Distributed computing power system driven by offshore wind power and data processing method

Abstract

The invention relates to a distributed computing power system driven by offshore wind power and a data processing method. The system comprises a land data center and a plurality of offshore data processing devices connected with the land data center, the offshore data processing device comprises a data processing module, an offshore wind power generation module and an emergency power supply module; the offshore wind power generation module is respectively connected with the data processing module and the emergency power supply module and is used for respectively supplying power to the data processing module and the emergency power supply module according to a power supply strategy from the land data center; the land data center is used for acquiring a calculation task and sending the calculation task to the corresponding offshore data processing device according to an allocation strategy; and when the data processing module of the offshore data processing device processes the calculation task to obtain a calculation result, the calculation result corresponding to the calculation task is sent to the land data center. According to the invention, the construction and operation cost of a computing power system and a data center can be effectively reduced.

Description

Technical Field

[0001] The present application relates to the field of computing technology, and in particular to a distributed computing power system and data processing method driven by offshore wind power. Background Art

[0002] With the widespread application of AI (Artificial Intelligence), data centers have become the core of modern information technology, and their energy consumption has become increasingly prominent. To maintain high computing power, data centers currently have a significant demand for electricity. Relying on traditional power generation methods (such as thermal power) for power supply solutions will result in high operating costs for high-performance data centers, hindering their promotion and deployment.

[0003] In addition, offshore wind power systems can also be used. By laying submarine cables, the wind power generated at sea is transmitted to the land power grid and then used to power the data center. Although this method can use clean and cheap electricity to maintain the operation of the data center, its infrastructure construction costs are high, and the submarine cables also have problems such as difficult maintenance. Summary of the Invention

[0004] Based on this, it is necessary to address the above technical problems and provide an offshore wind power-driven distributed computing system and data processing method that can reduce the construction and operation and maintenance costs of data centers.

[0005] In a first aspect, in one embodiment, the present application provides an offshore wind power-driven distributed computing system, the system comprising a land data center and a plurality of offshore data processing devices connected to the land data center, wherein the offshore data processing devices are disposed in a tower of an offshore wind turbine generator set;

[0006] The offshore data processing device includes a data processing module, an offshore wind power generation module, and an emergency power supply module; the offshore wind power generation module is connected to the data processing module and the emergency power supply module respectively, and is used to supply power to the data processing module and the emergency power supply module respectively according to the power supply strategy of the land data center;

[0007] Among them, the land data center is used to obtain computing tasks and send the computing tasks to the corresponding offshore data processing device according to the allocation strategy; when the data processing module of the offshore data processing device processes the computing tasks and obtains the computing results, the computing results corresponding to the computing tasks are sent to the land data center.

[0008] In one embodiment, the offshore data processing device further includes an offshore wireless communication module connected to the data processing module; the offshore wireless communication module establishes a wireless communication connection with a land wireless communication module of the land data center.

[0009] In one embodiment, the marine wireless communication module and the land wireless communication module are both microwave communication modules.

[0010] In one embodiment, the marine wireless communication module and the land wireless communication module are both satellite communication modules.

[0011] In one embodiment, the data processing module is used to assign task priorities to computing tasks; the task priorities are determined based on the urgency of the computing tasks, the computational complexity, and user requirements.

[0012] In one embodiment, the data processing module is used to dynamically adjust CPU resources and GPU resources according to the power supply capacity and task priority of the offshore wind power generation module, and allocate container resources through virtualization technology.

[0013] In one embodiment, the offshore data processing device further includes a wind speed sensor connected to the data processing module, the wind speed sensor being configured to send collected wind speed data near the tower to the data processing module;

[0014] Among them, the data processing module transmits wind speed data to the land data center; the land data center feeds back control information to the data processing module based on the wind speed data and the communication quality of the offshore wireless communication module; the data processing module adjusts the working mode of the offshore wireless communication module and the offshore wind power generation module according to the control information.

[0015] In one embodiment, the emergency power supply module includes a battery management unit, which is used to obtain power status data of the emergency power supply module and send the power status data to the data processing module;

[0016] The land data center receives power status data from the data processing module, and feeds back the power supply strategy to the data processing module based on the power status data and computing task requirements.

[0017] In one embodiment, each offshore data processing device and the land-based data center form a star topology;

[0018] The land-based data center acts as a central node in a star topology to manage the task allocation and data reception of all offshore data processing devices.

[0019] In a second aspect, in one embodiment, a data processing method is applied to the distributed computing system as described in any one of the above embodiments, and the method includes:

[0020] In response to obtaining the computing task, the land data center is used to send the computing task to the corresponding offshore data processing device according to the allocation strategy;

[0021] When the calculation task is processed and the calculation result is obtained, the offshore data processing device sends the calculation result corresponding to the calculation task to the land data center.

[0022] The above-mentioned distributed computing system and data processing method driven by offshore wind power processes computing tasks from a land-based data center through multiple offshore data processing devices driven by offshore wind power, and feeds the computing results obtained from the processing tasks back to the land-based center. This application can significantly reduce the construction and operation and maintenance costs of data centers through the above-mentioned method. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application or related technologies, the following briefly introduces the drawings required for use in the embodiments of the present application or related technical descriptions. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other related drawings can be obtained based on these drawings without paying any creative work.

[0024] Figure 1 1 is a schematic structural diagram of a distributed computing power system driven by offshore wind power in one embodiment;

[0025] Figure 2 Schematic diagram of the structure of another distributed computing system driven by offshore wind power in one embodiment;

[0026] Figure 3 A schematic structural diagram of an offshore data processing device according to an embodiment;

[0027] Figure 4 The figure is a flow chart of a data processing method in one embodiment. DETAILED DESCRIPTION

[0028] To facilitate understanding of the present application, the present application will be described more fully below with reference to the accompanying drawings. The accompanying drawings provide embodiments of the present application. However, the present application may be implemented in many different forms and is not limited to the embodiments described herein. Rather, these embodiments are provided to make the disclosure of the present application more thorough and comprehensive.

[0029] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application pertains. The terms used herein in the specification of this application are for the purpose of describing specific embodiments only and are not intended to limit this application.

[0030] It can be understood that the “connection” in the following embodiments should be understood as “electrical connection”, “communication connection”, etc. if there is transmission of electrical signals or data between the connected circuits, modules, units, etc.

[0031] It is understood that “at least one” refers to one or more, “a plurality” refers to two or more, and “at least a portion of an element” refers to a portion or all of an element.

[0032] In one embodiment, Figure 1 As shown, the present application provides a distributed computing system 10 driven by offshore wind power, the system comprising a land data center 100 and a plurality of offshore data processing devices 200 connected to the land data center, the offshore data processing devices 200 being arranged in the tower of the offshore wind turbine generator set;

[0033] The offshore data processing device 200 includes a data processing module 202, an offshore wind power generation module 204, and an emergency power supply module 206. The offshore wind power generation module 204 is connected to the data processing module 202 and the emergency power supply module 206, respectively, and is used to power the data processing module 202 and the emergency power supply module 206 according to the power supply strategy of the land data center 100.

[0034] Among them, the land data center 100 can be used to obtain computing tasks and send the computing tasks to the corresponding offshore data processing device 200 according to the allocation strategy; when the data processing module 202 of the offshore data processing device 200 processes the computing tasks to obtain computing results, the computing results corresponding to the computing tasks are sent to the land data center 100.

[0035] Specifically, when the land data center 100 receives a computing task, it will send the computing task to the corresponding offshore data processing device 200 according to the preset allocation strategy. The corresponding offshore data processing device 200 can use its data processing module 202 to process the received computing task and return the computing result corresponding to the computing task to the land data center 100.

[0036] Illustratively, the offshore wind power generation module 204 may include a foundational wind turbine structure and a wind turbine generator connected thereto, and the data processing module 202 may include locally located servers and storage devices. Optionally, based on the power supply strategy from the land-based data center 100, the offshore wind power generation module 204 may prioritize the generated electricity for the local servers and storage devices in the data processing module 202, while the remaining power may be used to charge the emergency power supply module 206. In some examples, the emergency power supply module 206 may adaptively adjust the battery's charge and discharge status based on the power supply strategy from the land-based data center 100 to extend the life of the emergency power supply module 206.

[0037] In some possible implementations, the land-based data center 100 may receive computing tasks issued by user terminals via the Internet and send the computing tasks to the corresponding offshore data processing device 200 according to the allocation strategy. For example, the computing tasks may include cloud computing, edge computing, artificial intelligence training, etc.; the data format of the computing tasks may be structured data or unstructured data; and the data types of the computing tasks may include text, images, audio, and video.

[0038] In some examples, the allocation strategy of the land data center 100 may be: classifying received computing tasks; allocating computing tasks with lower computational complexity to offshore data processing devices 200 with lower computing power performance; allocating computing tasks with higher computational complexity to offshore data processing devices 200 with higher computing power performance; or allocating computing tasks with higher computational complexity to multiple offshore data processing devices 200 for distributed parallel computing. It is understood that the allocation strategy of the land data center 100 is not limited to the implementation methods mentioned in the above embodiments. As long as it can achieve the function of allocating computing tasks received by the land data center 100 to appropriate offshore data processing devices 200 to achieve efficient computing, the embodiments of the present application do not limit the specific implementation method of the allocation strategy.

[0039] In the above-mentioned distributed computing power system driven by offshore wind power, after receiving a computing task, the land data center 100 can send the computing task to the corresponding offshore data processing device 200 according to a preset allocation strategy. The corresponding offshore data processing device 200 can then use its data processing module 202 to process the received computing task and return the calculation result corresponding to the computing task to the land data center 100. Through the above-mentioned method, the present application can use clean offshore wind energy to power the high-consumption computing power system, thereby reducing the operating costs of the computing power center. In addition, the system of the present application adopts a distributed topology structure, which can further improve the system's ability to handle complex computing tasks, allowing the computing power system to maintain or even improve the system's computing power performance while reducing the system's operating costs.

[0040] In one embodiment, the offshore data processing device 200 further includes a marine wireless communication module 208 connected to the data processing module 202 ; the marine wireless communication module 208 establishes a wireless communication connection with the land wireless communication module 102 of the land data center 100 .

[0041] Specifically, the land-based wireless communication module 102 of the land-based data center 100 can transmit data information such as pending computing tasks and power supply strategies to the offshore wireless communication module 208 of the offshore data processing device 200 via a wireless communication link. The offshore wireless communication module 208 can then return the corresponding computational results of the computing tasks via the wireless communication link. In some examples, the offshore wireless communication module 208 and the land-based wireless communication module 102 also support functions such as sending commands and updating program packages.

[0042] It can be understood that compared with the method of using submarine cables for communication, the land data center 100 and the offshore data processing device 200 in the embodiment of the present application use wireless communication links to interact with data without laying expensive submarine cables, thereby greatly reducing the construction and operation and maintenance costs of the computing system.

[0043] In one embodiment, both the marine wireless communication module 208 and the terrestrial wireless communication module 102 are microwave communication modules.

[0044] For example, the microwave communication module may include a microwave transmitting antenna, a receiving antenna, and a signal modem. In some examples, the microwave communication module uses a high-frequency microwave link for communication. Optionally, the high-frequency microwave link may be a Ka-band or E-band microwave link.

[0045] Specifically, the microwave communication module can utilize the microwave communication link to achieve efficient point-to-point bidirectional data interaction between the land data center 100 and the offshore data processing device 200 .

[0046] In one embodiment, both the marine wireless communication module 208 and the terrestrial wireless communication module 102 are satellite communication modules.

[0047] Specifically, for deep seas more than 80 km offshore, the performance of microwave communications is relatively weak. The marine wireless communication module 208 and the land wireless communication module 102 of the embodiment of the present application can use satellite communication modules to establish wireless communication connections, thereby increasing the constructible scope of the computing power system of the present application, and further increasing the versatility of the computing power system of the present application.

[0048] In one embodiment, the data processing module 202 is used to assign task priorities to computing tasks; the task priorities are determined based on the urgency of the computing tasks, the computational complexity, and user requirements.

[0049] Specifically, when data processing module 202 receives a computing task from land-based data center 100, it can assign a priority to the computing task based on its urgency, computational complexity, and current user needs. When data processing module 202 has multiple computing tasks to process, it can determine the order in which the tasks are processed based on the priority of each task. This embodiment of the present application effectively improves the computing efficiency of offshore data processing device 200 through the above-described approach.

[0050] In one embodiment, the data processing module 202 is configured to dynamically adjust CPU resources and GPU resources according to the power supply capability and task priority of the offshore wind power generation module 204 , and allocate container resources through virtualization technology.

[0051] For example, when the power supply capacity of the wind power generation module is insufficient (for example, the wind speed is low, the battery storage power is insufficient), the data processing module 202 may enable only part of the CPU resources and GPU resources to process a single computing task with a higher task priority; when the power supply capacity of the wind power generation module is strong, the data processing module 202 may enable all CPU resources and GPU resources to process multiple computing tasks with higher task priorities in parallel, and allocate more container resources through virtualization technology to improve computing efficiency.

[0052] Specifically, the data processing module 202 dynamically adjusts the server's CPU (Central Processing Unit) resources and GPU (Graphics Processing Unit) resources according to the power supply capacity and task priority of the offshore wind power generation module 204, and allocates container resources through virtualization technology, thereby improving the computing power system's ability to adapt to different power supply environments and further improving the reliability of the computing power system.

[0053] In one embodiment, Figure 3 As shown, the offshore data processing device 200 further includes a wind speed sensor 210 connected to the data processing module 202 . The wind speed sensor 210 is used to send the collected wind speed data near the tower to the data processing module 202 .

[0054] Among them, the data processing module 202 transmits the wind speed data to the land data center 100; the land data center 100 feeds back control information to the data processing module 202 based on the wind speed data and the communication quality of the offshore wireless communication module 208; the data processing module 202 adjusts the working mode of the offshore wireless communication module 208 and the offshore wind power generation module 204 according to the control information.

[0055] For example, the land data center 100 can use a machine learning algorithm to predict the wind speed based on the received wind speed data, and based on the wind speed data and the wind speed prediction results, generate control information for dynamically adjusting the wind turbine speed and pitch angle of the offshore wind power generation module 204, so that the power generation efficiency of the offshore wind power generation module 204 can be optimized by adjusting the wind turbine speed and pitch angle.

[0056] Furthermore, the land data center 100 can obtain communication quality information of the marine wireless communication module 208 and dynamically adjust the transmit power, modulation mode, and frequency band selection of the marine wireless communication module 208 based on the communication quality information of the marine wireless communication module 208. Optionally, the marine wireless communication module 208 and the land wireless communication module 102 can also utilize adaptive antenna technology to further improve signal reception.

[0057] In some possible implementations, if the land data center 100 determines based on monitoring data such as wind speed data that the offshore data processing device 200 is in extreme weather, or if an abnormality occurs in the offshore data processing device 200, remote intervention can be performed via a wireless communication link to switch the offshore data processing device 200 to the lowest power consumption mode or a preset safety mode to protect the equipment.

[0058] In one embodiment, the emergency power module 206 includes a battery management unit, which is used to obtain power status data of the emergency power module 206 and send the power status data to the data processing module 202;

[0059] The land data center 100 receives the power status data from the data processing module 202 and feeds back a power supply strategy to the data processing module 202 based on the power status data and computing task requirements.

[0060] In some examples, the emergency power module 206 may include a set of high-capacity batteries that can maintain normal operation of key system modules in the event of insufficient wind speed or equipment failure such as a wind turbine structure.

[0061] Specifically, the battery management unit of the emergency power supply module 206 collects the power status data of the emergency power supply module 206 and sends the obtained power status data to the data processing module 202; when the land data center 100 receives the power status data from the data processing module 202, it can feedback the power supply strategy to the data processing module 202 based on the power status data of the emergency power supply module 206 and the current computing task requirements; the data processing module 202 can adjust the charging and discharging working status of the emergency power supply module 206 according to the power supply strategy, thereby protecting the battery of the emergency power supply module 206 and extending the service life of the battery.

[0062] In one embodiment, each offshore data processing device 200 and the land data center 100 form a star topology;

[0063] The land data center 100 serves as a central node in the star topology to manage task allocation and data reception of all offshore data processing devices 200 .

[0064] Specifically, the land-based data center 100 serves as a central node, forming a star topology with the connected offshore data processing devices 200. By configuring the distributed computing system in a star topology, the present embodiment reduces the complexity of adding new offshore data processing devices 200, effectively improving the system's scalability. Furthermore, the star topology facilitates troubleshooting and repair in the event of a system failure.

[0065] In one example, the present application provides a data center comprising a distributed computing power system driven by offshore wind power as described in any of the above system embodiments.

[0066] It can be understood that the implementation solution provided by the data center to solve the problem is similar to the implementation solution recorded in the above system embodiment. For specific limitations, please refer to the above limitations on the distributed computing power system driven by offshore wind power, which will not be repeated here.

[0067] Based on the above-mentioned distributed computing power system driven by offshore wind power, the present application can at least achieve the following technical effects: 1. The present application realizes data transmission between land data centers and offshore data processing devices through wireless communication links (including microwave communication links and satellite communication links), avoiding the use of submarine cables. 2. The present application uses the electric energy generated by the offshore wind power generation module to directly power the server and storage of the data processing module to complete the processing of computing tasks. In this way, the need for long-distance power transmission is avoided, the construction cost of the computing power system and the data center is reduced, and it is also beneficial to the subsequent system maintenance. 3. The system of the present application adopts a distributed topology structure, which can improve the computing power system's ability to handle complex computing tasks, so that the computing power system can maintain or even improve the system's computing power performance while reducing the system's operating costs.

[0068] Based on the same inventive concept, the present application also provides a data processing method based on the above-mentioned distributed computing system driven by offshore wind power. The implementation solution provided by this method is similar to the implementation solution described in the above-mentioned embodiment. Therefore, the specific limitations of one or more data processing method embodiments provided below can be referred to the above-mentioned limitations of the distributed computing system driven by offshore wind power, and will not be repeated here.

[0069] In one embodiment, Figure 4 As shown, a data processing method is applied to the distributed computing system as described in any one of the above embodiments, and the method includes the following steps S402 to S404.

[0070] Step S402 : In response to obtaining the computing task, the land data center 100 is configured to send the computing task to the corresponding offshore data processing device 200 according to the allocation strategy.

[0071] In step S404 , when the calculation task is processed and a calculation result is obtained, the offshore data processing device 200 sends the calculation result corresponding to the calculation task to the land data center 100 .

[0072] It should be understood that, although the various steps in the flowcharts involved in the various embodiments described above are displayed in sequence according to the instructions of the arrows, these steps are not necessarily executed in sequence in the order indicated by the arrows. Unless otherwise specified herein, there is no strict order restriction on the execution of these steps, and these steps can be executed in other orders. Moreover, at least a portion of the steps in the flowcharts involved in the various embodiments described above can include multiple steps or multiple stages, and these steps or stages are not necessarily executed and completed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily to be carried out in sequence, but can be executed in turn or alternately with other steps or at least a portion of steps or stages in other steps.

[0073] In one embodiment, a computer device is further provided, including a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0074] In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a processor, the steps in the above-mentioned method embodiments are implemented.

[0075] In one embodiment, a computer program product is provided, including a computer program, which implements the steps in the above method embodiments when executed by a processor.

[0076] Those skilled in the art will understand that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above-mentioned methods. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile memory and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), quantum computing-based data processing logic devices, artificial intelligence (AI) processors, and the like.

[0077] The technical features of the above embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this application.

[0078] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present application shall be determined by the appended claims.

Claims

1. A distributed computing system driven by offshore wind power, characterized in that: The system includes a land data center and a plurality of offshore data processing devices connected to the land data center, wherein the offshore data processing devices are arranged in a tower of an offshore wind turbine generator set; The offshore data processing device includes a data processing module, an offshore wind power generation module, and an emergency power supply module; the offshore wind power generation module is connected to the data processing module and the emergency power supply module, respectively, and is used to supply power to the data processing module and the emergency power supply module according to the power supply strategy from the land data center; Among them, the land data center is used to obtain computing tasks and send the computing tasks to the corresponding offshore data processing device according to the allocation strategy; when the data processing module of the offshore data processing device processes the computing tasks and obtains computing results, the computing results corresponding to the computing tasks are sent to the land data center.

2. The system according to claim 1, wherein: The offshore data processing device further includes a marine wireless communication module connected to the data processing module; the marine wireless communication module establishes a wireless communication connection with the land wireless communication module of the land data center.

3. The system according to claim 2, characterized in that The marine wireless communication module and the land wireless communication module are both microwave communication modules.

4. The system according to claim 2, wherein: The marine wireless communication module and the land wireless communication module are both satellite communication modules.

5. The system according to claim 2, wherein: The data processing module is used to assign task priorities to the computing tasks; the task priorities are determined based on the urgency, computational complexity and user requirements of the computing tasks.

6. The system according to claim 5, characterized in that The data processing module is used to dynamically adjust CPU resources and GPU resources according to the power supply capacity of the offshore wind power generation module and the task priority, and allocate container resources through virtualization technology.

7. The system according to claim 2, wherein: The offshore data processing device further includes a wind speed sensor connected to the data processing module, wherein the wind speed sensor is used to send the collected wind speed data near the tower to the data processing module; Among them, the data processing module transmits the wind speed data to the land data center; the land data center feeds back control information to the data processing module based on the wind speed data and the communication quality of the offshore wireless communication module; the data processing module adjusts the working mode of the offshore wireless communication module and the offshore wind power generation module according to the control information.

8. The system according to claim 1, wherein: The emergency power supply module includes a battery management unit, which is used to obtain the power status data of the emergency power supply module and send the power status data to the data processing module; The land data center receives the power status data from the data processing module, and feeds back the power supply strategy to the data processing module based on the power status data and computing task requirements.

9. The system according to any one of claims 1 to 8, characterized in that Each of the offshore data processing devices and the land data center forms a star topology structure; The land data center serves as a central node in the star topology to manage task allocation and data reception of all the offshore data processing devices.

10. A data processing method, characterized in that: The method is applied to the distributed computing system according to any one of claims 1 to 9, and the method includes: In response to obtaining the computing task, the land data center is used to send the computing task to the corresponding offshore data processing device according to the allocation strategy; When the computing task is processed to obtain a computing result, the offshore data processing device sends the computing result corresponding to the computing task to the land data center.

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