Data center computing power regulation and control method based on new energy and related device

Abstract

The invention discloses a data center computing power regulation and control method based on new energy and a related device. The method comprises the following steps: setting each computing power priority level based on emergency degree and importance degree in advance; for each computing power event, determining a target computing power priority level corresponding to the computing power event based on each computing power priority level; determining a power utilization strategy and a computing power distribution scheme based on the system parameters of the data center, the generated power prediction parameters of the new energy station and the power grid parameters of the current region; and acquiring a processable computing power priority level in the computing power distribution scheme, traversing each computing power event to search a target computing power event of which the target computing power priority level is included in the processable computing power priority level, and regulating and controlling the target computing power event based on the power utilization strategy and the computing power distribution scheme. According to the above process, the computing power priority level is preset, regulation and control are carried out only for the target computing power event selected according to the computing power priority level, regulation and control are not carried out for all computing power events, regulation and control are more reasonable, and waste of new energy is avoided.

Description

Technical Field

[0001] The present invention relates to the field of electric power technology, and in particular to a data center computing power control method based on new energy and related devices. Background Art

[0002] In recent years, the construction of new energy power stations represented by photovoltaic and wind power has increased rapidly, involving almost all provinces and regions. However, photovoltaic and wind power generation have inherent defects such as volatility and intermittency, which poses a huge challenge to the stability of the power grid. The power grid has to start and stop thermal power for flexible adjustment.

[0003] With the development of my country's Internet and big data industries, more and more data centers are being built, and the demand for electricity in data centers is also increasing. How to coordinate and regulate electricity and computing power is a key measure for the green development of new energy. If the computing power and electricity are not allocated reasonably, it will lead to the waste of new energy. Summary of the invention

[0004] In view of this, the present invention provides a data center computing power control method and related devices based on new energy, which are used to solve the problem in the prior art that unreasonable computing power and power distribution will lead to waste of new energy. The specific scheme is as follows:

[0005] A data center computing power control method based on new energy, applied to new energy sites, comprising:

[0006] Pre-set various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent, and ordinary generally urgent;

[0007] Obtain each computing power event of the data center, and determine a corresponding target computing power priority level for each computing power event based on each computing power priority level;

[0008] Obtaining system parameters of the data center, power generation prediction parameters of the new energy site, and power grid parameters of the current area, and determining a power consumption strategy and a computing power allocation plan based on the system parameters, the power generation prediction parameters, and the power grid parameters;

[0009] Obtain the processable computing power priority level included in the computing power allocation plan, traverse the various computing power events to find the target computing power event whose target computing power priority level is included in the processable computing power priority level, and regulate the target computing power event based on the power consumption strategy and the computing power allocation plan.

[0010] The above-mentioned data center computing power control method based on new energy sources may optionally determine the power consumption strategy and computing power allocation plan based on the system parameters, the power generation power prediction parameters and the power grid parameters, including:

[0011] Sending the system parameters, the power generation prediction parameters and the grid parameters to a preset computing power allocation model, wherein the preset computing power allocation model is trained based on historical computing power sample data;

[0012] Obtain the power usage strategy and computing power allocation plan output by the preset computing power model, wherein the power usage strategy includes: available new energy power, and the computing power allocation plan includes: a priority level of processable computing power.

[0013] The above-mentioned data center computing power control method based on new energy sources may optionally control the target computing power event based on the power consumption strategy and the computing power allocation scheme, including:

[0014] Obtaining the available new energy power included in the power usage strategy and the computing power required for each target computing power event, wherein there is a corresponding relationship between the available new energy power and the computing power;

[0015] Comparing the available new energy power with a preset power threshold;

[0016] If the new energy power is less than the preset power threshold, it is determined that the new energy power is in the first power state, and the data center allocates the corresponding new energy power to the target computing power event based on the corresponding relationship.

[0017] The above-mentioned data center computing power control method based on new energy sources may optionally control the target computing power event based on the power consumption strategy and the computing power allocation plan, and further include:

[0018] If the new energy power is greater than the preset power threshold, it is determined that the available new energy power is in the second power state, and the data center allocates the corresponding new energy power to all computing power events based on the corresponding relationship.

[0019] The above-mentioned data center computing power control method based on new energy sources may optionally control the target computing power event based on the power consumption strategy and the computing power allocation plan, and further include:

[0020] If the power of the new energy is 0, the data center is connected to the mains, and the target computing power event is regulated based on the event.

[0021] The above-mentioned data center computing power control method based on new energy may optionally further include:

[0022] Obtaining the power generation capacity of the new energy station and the computing power of the data center;

[0023] The power generation capacity is set to be higher than the computing power and the difference between the two is within a preset range.

[0024] A data center computing power control device based on new energy, applied to new energy sites, comprising:

[0025] A setting module is used to pre-set various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent and ordinary generally urgent;

[0026] A first acquisition and determination module is used to acquire each computing power event of the data center, and determine the corresponding target computing power priority level for each computing power event based on the computing power priority levels;

[0027] A second acquisition and determination module is used to acquire the system parameters of the data center, the power generation prediction parameters of the new energy site and the power grid parameters of the current area, and determine the power consumption strategy and computing power allocation plan based on the system parameters, the power generation prediction parameters and the power grid parameters;

[0028] A control module is used to obtain the processable computing power priority level included in the computing power allocation plan, traverse the various computing power events to find the target computing power event whose target computing power priority level is included in the processable computing power priority level, and control the target computing power event based on the power consumption strategy and the computing power allocation plan.

[0029] In the above-mentioned data center computing power control device based on new energy, optionally, the second acquisition and determination module includes:

[0030] A sending unit, used to send the system parameter, the power generation prediction parameter and the grid parameter to a preset computing power allocation model, wherein the preset computing power allocation model is trained based on historical computing power sample data;

[0031] The first acquisition unit is used to obtain the power usage strategy and the computing power allocation plan output by the preset computing power model, wherein the power usage strategy includes: available new energy power, and the computing power allocation plan includes: a priority level of processable computing power.

[0032] The above-mentioned data center computing power control device based on new energy, optionally, the control module includes:

[0033] A second acquisition unit is used to acquire the available new energy power included in the power consumption strategy and the computing power required for each target computing power event, wherein there is a corresponding relationship between the available new energy power and the computing power;

[0034] A comparison unit, configured to compare the available new energy power with a preset power threshold;

[0035] The first determination unit is used to determine that the new energy power is in a first power state if the new energy power is less than the preset power threshold, and the data center allocates the corresponding new energy power to the target computing power event based on the corresponding relationship.

[0036] The above-mentioned data center computing power control device based on new energy, optionally, the control module further includes:

[0037] The second determination unit is configured to determine that the available new energy power is in a second power state if the new energy power is greater than the preset power threshold. The data center allocates the corresponding new energy power to all computing power events based on the corresponding relationship.

[0038] A storage medium, the storage medium comprising a stored program, wherein the program executes the above-mentioned data center computing power regulation method based on new energy.

[0039] A processor is used to run a program, wherein the program executes the above-mentioned data center computing power regulation method based on new energy when running.

[0040] Compared with the prior art, the present invention has the following advantages:

[0041] The present invention discloses a data center computing power control method and related devices based on new energy, which are applied to new energy sites, including: pre-setting various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent and ordinary generally urgent; obtaining various computing power events of the data center, and determining the corresponding target computing power priority level for each computing power event based on the various computing power priority levels; obtaining system parameters of the data center, power generation prediction parameters of the new energy site and power grid parameters of the current area, and determining a power consumption strategy and a computing power allocation plan based on the system parameters, the power generation prediction parameters and the power grid parameters; obtaining the processable computing power priority levels contained in the computing power allocation plan, traversing the various computing power events to find the target computing power event whose target computing power priority level is contained in the processable computing power priority level, and regulating the target computing power event based on the power consumption strategy and the computing power allocation plan. In the above process, the computing power priority level is pre-set. During the regulation process, only the target computing power events selected according to the computing power priority level are regulated, and not all computing power events are regulated. The regulation is more reasonable and avoids the waste of new energy. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0043] Figure 1 A schematic diagram of the connection relationship between a data center, a new energy station and a power grid in the prior art;

[0044] Figure 2 A flow chart of a data center computing power control method based on new energy disclosed in an embodiment of the present invention;

[0045] Figure 3 A schematic diagram of a data center computing power priority level classification disclosed in an embodiment of the present invention;

[0046] Figure 4 A schematic diagram of the collaboration between new energy power generation and a data center disclosed in an embodiment of the present application;

[0047] Figure 5 This is a structural block diagram of a data center computing power control device based on new energy disclosed in an embodiment of the present invention;

[0048] Figure 6The present invention is a schematic diagram of a device disclosed in an embodiment of the present invention. DETAILED DESCRIPTION

[0049] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0050] The present invention discloses a data center computing power control method and related devices based on new energy, which are applied to control the computing power of the data center based on new energy, solving the problem of coordination between computing power and power dispatch in the prior art, avoiding waste of new energy, and solving the impact of the volatility and instability of existing new energy power generation on the load consumption side, and also providing a new solution for the flexibility regulation of new energy power generation. The method is applied to new energy stations, and the connection relationship between the new energy stations and the data center and the power grid is shown in the figure below. Figure 1 As shown, it includes: a new energy station, a power grid and a data center. The new energy station can be a wind power plant, a photovoltaic power plant or a wind-solar complementary power plant. In the embodiment of the present invention, the new energy station is taken as a wind-solar complementary power plant as an example for explanation. The new energy station includes: a photovoltaic power generation array, a wind turbine generator set and a substation.

[0051] In the embodiment of the present invention, the method is applied to a new energy station, the computing power of the data center is basically matched with the power generation capacity of the new energy station, the power generation capacity of the new energy station can be slightly higher than the computing power of the data center, and the power generation capacity is set to be higher than the computing power and the difference between the two is within a preset interval. Among them, the preset interval can be set based on experience or specific circumstances, and is not specifically limited in the embodiment of the present invention. The power supply bus of the data center is connected to both the transmission line of the new energy power station and the mains power supply line. When the data center uses electricity, the mains power and the new energy power supply can be supplied at the same time or separately; the power generation transmission line of the new energy station is connected to both the power supply bus of the data center and the power grid transmission line. When the new energy station generates electricity, the electric energy can be used and sent out by the data center at the same time, or it can be used by the data center alone, or it can be sent out to the power grid alone; the new energy station has a complete wind and solar power prediction system, which can realize long-term, short-term, and ultra-short-term power prediction. Wind and solar power prediction refers to the prediction of wind and solar power generation of new energy power stations, which mainly predicts the changes in wind and solar power generation at the next moment or in a certain period of time in the future. Based on the predicted changes in wind and solar power generation, it can be used to feedback and regulate the amount of computing power input at the next moment. The data center can allocate real-time computing power according to the computing power priority level and power supply; when the data center uses municipal electricity, the electricity is purchased at the real-time electricity price or the agreed electricity price; when the power generated by the new energy station is sent to the power grid, the electricity is sold at the real-time electricity price or the agreed electricity price; an efficient scheduling information and collaborative interaction system is established between the data center and the new energy station, which can realize the information interaction between real-time electricity and computing power;

[0052] The execution flow of the method is as follows: Figure 2 As shown, including:

[0053] S101. Pre-set various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent, and ordinary generally urgent;

[0054] In the embodiment of the present invention, the urgency and importance can be defined based on experience or specific application scenarios, and are not specifically limited in the embodiment of the present invention. In the embodiment of the present invention, the urgency is divided into three levels, including: urgent, relatively urgent and generally urgent, and the importance is divided into three levels, including: ordinary, important and core. The levels included in the urgency and the importance are combined in pairs to divide them into various computing power priority levels, such as Figure 3 As shown, including: core emergency, core more urgent, core general emergency, important emergency, important more urgent, important general emergency, ordinary emergency, ordinary more urgent and ordinary general emergency, according to Figure 3The order of ①-⑨ decreases in importance and urgency.

[0055] S102, obtaining each computing power event of the data center, and determining a corresponding target computing power priority level for each computing power event based on each computing power priority level;

[0056] In the embodiments of the present invention, for specific application scenarios, each application scenario will correspond to multiple computing power events, each computing power event is used to implement related functions, and for each computing power event, a target computing power priority level is selected from the various computing power priority levels according to its importance and urgency. Among them, for different application scenarios, the same computing power event can belong to different target computing power priority levels. The selection principle for the target computing power priority level can be selected based on the specific situation, and is not specifically limited in the embodiments of the present invention.

[0057] S103, obtaining system parameters of the data center, power generation prediction parameters of the new energy site, and power grid parameters of the current area, and determining a power consumption strategy and a computing power allocation plan based on the system parameters, the power generation prediction parameters, and the power grid parameters;

[0058] In an embodiment of the present invention, system parameters of the data center are obtained at a first preset position, wherein the system parameters include: computing power classification, power consumption, etc.; power generation prediction parameters of the new energy site are obtained at a second preset position, wherein the power generation prediction parameters include: long-time, short-time, ultra-short-time and other data; the specific values ​​of the long-time, the short-time and the ultra-short-time can be set based on experience or specific circumstances, and are not specifically limited in the embodiment of the present invention; power grid parameters of the current area are obtained at a third preset position, wherein the power grid parameters include: grid power quality, regional power grid power, electricity price, etc., wherein the determination of the first preset position, the second preset position and the third preset position is related to the specific application scenario, and are not specifically limited in the embodiment of the present invention.

[0059] Further, after the system parameters, the power generation prediction parameters and the grid parameters are determined, the power consumption strategy and the computing power allocation scheme are determined based on the system parameters, the power generation prediction parameters and the grid parameters. The specific processing process is as follows:

[0060] The system parameters, the power generation prediction parameters and the grid parameters are sent to the preset computing power allocation model, wherein the preset computing power allocation model is obtained by training based on historical computing power sample data, and the preset computing power allocation model contains boundary constraints, which can be set based on specific application scenarios, and are not specifically limited in the embodiments of the present invention. The preset computing power allocation model obtains the optimal electric energy and computing power allocation results based on boundary constraints such as computing power importance, electricity economy, and data center operation stability. The calculation process can be carried out in the data center, and the specific implementation method is to calculate based on the current and future electricity price fluctuations, new energy power generation forecast power generation and volatility. The entire system can be implemented using one or more intelligent control strategies.

[0061] In the embodiment of the present invention, the importance of computing power refers to the importance or priority of the computing case and task target in the entire system, and the degree of influence on the entire system. The specific acquisition method is defined by the user side and does not require judgment by this application. The economy of electricity use refers to the peak and valley electricity prices. The use of low electricity prices can achieve the best economy. The specific acquisition method is based on the electricity prices released by the power grid. Stable operation of the data center means that in a relatively short period of time, the volatility of computing power will not fluctuate greatly, that is, the output power will not change suddenly.

[0062] In the embodiment of the present invention, the specific existence form of the preset computing power allocation model is not limited. After determining the preload computing power allocation model, training is performed based on historical computing power samples, wherein the historical computing power samples include: historical system parameters, historical power generation prediction parameters and historical power grid parameters, and historical training strategies and historical computing power allocation schemes corresponding to the above historical parameters. The preset computing power allocation model is trained based on the historical computing power samples. In the embodiment of the present invention, the specific training process is not limited. After the training is completed, the power consumption strategy and computing power allocation scheme are determined based on the preset computing power allocation model. In the embodiment of the present invention, the preset computing power allocation model is used for wind and solar power prediction. The wind and solar power prediction refers to the use of meteorological center data, weather observation systems, etc., by calculating or measuring the wind speed, wind direction, light intensity, angle, etc. at the next moment, and calculating the power generation at the next moment. It is essentially a prediction of power generation. Long-term, short-term, and ultra-short-term predictions are mainly different in the prediction time scale, which are hourly, minute-level, and second-level, respectively. The specific implementation method is to collect a series of relevant meteorological data including but not limited to wind speed, wind direction, light intensity, radiance, light angle, temperature and humidity (the data source can be released by the local meteorological center or obtained by real-time measurement), and learn and predict through a series of optimization algorithms such as neural network, ant colony algorithm, genetic algorithm, etc. Obtain the power consumption strategy and computing power allocation plan output by the preset computing power model, wherein the power consumption strategy includes: available new energy power (the embodiment of the present invention refers to wind and solar power), and the computing power allocation plan includes: the priority level of processable computing power.

[0063] S104, obtaining the processable computing power priority level included in the computing power allocation plan, traversing the various computing power events to find the target computing power event whose target computing power priority level is included in the processable computing power priority level, and regulating the target computing power event based on the power consumption strategy and the computing power allocation plan.

[0064] In the embodiment of the present invention, preferably, the power strategy and the computing power allocation scheme are sent to the corresponding system in the form of an allocation instruction for regulation. The specific processing method is as follows: obtain the processable computing power priority level contained in the computing power allocation scheme, traverse the various computing power events to find the target computing power event whose target computing power priority level is included in the processable computing power priority level, obtain the available new energy power contained in the power strategy and the computing power required for each target computing power event, wherein there is a corresponding relationship between the available new energy power and the computing power, that is, each computing power event corresponds to a computing power, and each computing power corresponds to a new energy power. Compare the available new energy power with the preset power threshold; if the new energy power is less than the preset power threshold, it means that the power generation of the new energy site is low, determine that the new energy power processes the first power state, the data center only needs to run part of the computing power, and the computing power events of ordinary degree and general urgency can not be processed. Based on the corresponding relationship, the data center allocates the corresponding new energy power to the target computing power event that meets the above requirements.

[0065] If the new energy power is greater than the preset power threshold, it means that the power generation capacity of the new energy station is relatively sufficient, and the data center can invest all computing power and operate at full load. It is determined that the available new energy power is in the second power state. The data center allocates the corresponding new energy power to all computing power events based on the corresponding relationship.

[0066] If the power of the new energy source is 0, the data center is connected to the mains, and only the core and urgent computing power is operated, and the target computing power event is regulated based on the event. When the mains electricity price is lower than the cost of new energy power generation, the data center uses all the mains electricity, and the new energy power is sent to the nearest grid.

[0067] The present invention discloses a data center computing power control method based on new energy, which is applied to new energy sites, including: pre-setting various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent and ordinary generally urgent; obtaining various computing power events of the data center, and determining the corresponding target computing power priority level for each computing power event based on the various computing power priority levels; obtaining system parameters of the data center, power generation prediction parameters of the new energy site and power grid parameters of the current area, and determining a power consumption strategy and a computing power allocation plan based on the system parameters, the power generation prediction parameters and the power grid parameters; obtaining the processable computing power priority levels contained in the computing power allocation plan, traversing the various computing power events to find the target computing power event whose target computing power priority level is contained in the processable computing power priority level, and regulating the target computing power event based on the power consumption strategy and the computing power allocation plan. In the above process, the computing power priority level is pre-set. During the regulation process, only the target computing power events selected according to the computing power priority level are regulated, and not all computing power events are regulated. The regulation is more reasonable and avoids the waste of new energy.

[0068] In the embodiment of the present invention, Figure 4 As shown, the three platforms of data center, power grid and new energy station have the function of information exchange between important parameters; when the new energy station is generating electricity, it can send electricity to the power grid, and when it is not generating electricity, it can also purchase electricity from the power grid to maintain the basic operation of the station; when the new energy station is generating electricity, it can send electricity to the data center for use by the data center; the power grid can accept electricity from the new energy station, and can also supply electricity to the new energy station and the data bureau center.

[0069] Based on the above-mentioned data center computing power control method based on new energy, an embodiment of the present invention also provides a data center computing power control device based on new energy. The structural block diagram of the control device is as follows: Figure 5 As shown, it is applied to new energy stations, including:

[0070] A setting module 201 , a first obtaining and determining module 202 , a second obtaining and determining module 203 , and a regulating module 204 .

[0071] in,

[0072] The setting module 201 is used to pre-set various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent and ordinary generally urgent;

[0073] The first acquisition and determination module 202 is used to acquire each computing power event of the data center, and determine the corresponding target computing power priority level for each computing power event based on each computing power priority level;

[0074] The second acquisition and determination module 203 is used to acquire the system parameters of the data center, the power generation prediction parameters of the new energy site and the power grid parameters of the current area, and determine the power consumption strategy and computing power allocation plan based on the system parameters, the power generation prediction parameters and the power grid parameters;

[0075] The control module 204 is used to obtain the processable computing power priority level included in the computing power allocation plan, traverse the various computing power events to find the target computing power event whose target computing power priority level is included in the processable computing power priority level, and control the target computing power event based on the power consumption strategy and the computing power allocation plan.

[0076] The present invention discloses a data center computing power control device based on new energy, which is applied to new energy sites, including: pre-setting various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent and ordinary generally urgent; obtaining various computing power events of the data center, and determining the corresponding target computing power priority level for each computing power event based on the various computing power priority levels; obtaining system parameters of the data center, power generation prediction parameters of the new energy site and power grid parameters of the current area, and determining a power consumption strategy and a computing power allocation plan based on the system parameters, the power generation prediction parameters and the power grid parameters; obtaining the processable computing power priority levels contained in the computing power allocation plan, traversing the various computing power events to find the target computing power event whose target computing power priority level is contained in the processable computing power priority level, and regulating the target computing power event based on the power consumption strategy and the computing power allocation plan. In the above process, the computing power priority level is pre-set. During the regulation process, only the target computing power events selected according to the computing power priority level are regulated, and not all computing power events are regulated. The regulation is more reasonable and avoids the waste of new energy.

[0077] In the embodiment of the present invention, the second acquisition and determination module 203 includes:

[0078] A sending unit and a first acquiring unit.

[0079] in,

[0080] The sending unit is used to send the system parameters, the power generation prediction parameters and the power grid parameters to a preset computing power allocation model, wherein the preset computing power allocation model is obtained by training based on historical computing power sample data;

[0081] The first acquisition unit is used to obtain the power usage strategy and computing power allocation plan output by the preset computing power model, wherein the power usage strategy includes: available new energy power, and the computing power allocation plan includes: a priority level of processable computing power.

[0082] In the embodiment of the present invention, the control module 204 includes:

[0083] A second acquiring unit, a comparing unit and a first determining unit.

[0084] in,

[0085] The second acquisition unit is used to acquire the available new energy power included in the power consumption strategy and the computing power required for each target computing power event, wherein there is a corresponding relationship between the available new energy power and the computing power;

[0086] The comparison unit is used to compare the available new energy power with a preset power threshold;

[0087] The first determination unit is used to determine that the new energy power is in a first power state if the new energy power is less than the preset power threshold, and the data center allocates the corresponding new energy power to the target computing power event based on the corresponding relationship.

[0088] In the embodiment of the present invention, the control module 204 further includes: a second determination unit.

[0089] in,

[0090] The second determination unit is used to determine that the available new energy power is in the second power state if the new energy power is greater than the preset power threshold. The data center allocates the corresponding new energy power to all computing power events based on the corresponding relationship.

[0091] The control device includes a processor and a memory. The above-mentioned setting module, first acquisition and determination module, second acquisition and determination module and control module are all stored in the memory as program units, and the processor executes the above-mentioned program units stored in the memory to realize corresponding functions.

[0092] The processor contains a kernel, which calls the corresponding program unit from the memory. One or more kernels can be set, and the kernel parameters can be adjusted to achieve more reasonable regulation and avoid the problem of waste of new energy.

[0093] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory, such as read-only memory (ROM) or flash RAM, and the memory includes at least one memory chip.

[0094] An embodiment of the present invention provides a computer storage medium having a program stored thereon, which, when executed by a processor, implements the data center computing power regulation method based on new energy.

[0095] An embodiment of the present invention provides a processor, which is used to run a program, wherein the program executes the data center computing power regulation method based on new energy when running.

[0096] An embodiment of the present invention provides a device, the structural block diagram of which is as follows Figure 6 As shown, the device includes: a processor 301, a storage medium 302, and a program stored in the storage medium 302 and executable on the processor 302. When the processor 301 executes the program, the following steps are implemented:

[0097] Pre-set various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent, and ordinary generally urgent;

[0098] Obtain each computing power event of the data center, and determine a corresponding target computing power priority level for each computing power event based on each computing power priority level;

[0099] Obtaining system parameters of the data center, power generation prediction parameters of the new energy site, and power grid parameters of the current area, and determining a power consumption strategy and a computing power allocation plan based on the system parameters, the power generation prediction parameters, and the power grid parameters;

[0100] Obtain the processable computing power priority level contained in the computing power allocation scheme, traverse the various computing power events to find the target computing power priority level contained in the processable computing power priority level, and regulate the target computing power event based on the power consumption strategy and the computing power allocation scheme. It should be understood by those skilled in the art that the embodiments of the present application can be provided as methods, systems, or computer program products. Therefore, the present application may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0101] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0102] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0103] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0104] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0105] The memory may include non-permanent memory in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0106] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0107] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0108] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0109] The above are only embodiments of the present application and are not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included within the scope of the claims of the present application.

Claims

1. A data center computing power control method based on new energy, applied to new energy sites, characterized in that: include: Pre-set various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent, and ordinary generally urgent; Obtain each computing power event of the data center, and determine a corresponding target computing power priority level for each computing power event based on each computing power priority level; Obtaining system parameters of the data center, power generation prediction parameters of the new energy site, and power grid parameters of the current area, and determining a power consumption strategy and a computing power allocation plan based on the system parameters, the power generation prediction parameters, and the power grid parameters; Obtain the processable computing power priority level included in the computing power allocation plan, traverse the various computing power events to find the target computing power event whose target computing power priority level is included in the processable computing power priority level, and regulate the target computing power event based on the power consumption strategy and the computing power allocation plan.

2. The data center computing power control method based on new energy according to claim 1 is characterized in that: Determining a power consumption strategy and a computing power allocation scheme based on the system parameters, the power generation prediction parameters and the power grid parameters includes: Sending the system parameters, the power generation prediction parameters and the grid parameters to a preset computing power allocation model, wherein the preset computing power allocation model is trained based on historical computing power sample data; Obtain the power usage strategy and computing power allocation plan output by the preset computing power model, wherein the power usage strategy includes: available new energy power, and the computing power allocation plan includes: a priority level of processable computing power.

3. The data center computing power control method based on new energy according to claim 2 is characterized in that: The target computing power event is regulated based on the power usage strategy and the computing power allocation scheme, including: Obtaining the available new energy power included in the power usage strategy and the computing power required for each target computing power event, wherein there is a corresponding relationship between the available new energy power and the computing power; Comparing the available new energy power with a preset power threshold; If the new energy power is less than the preset power threshold, it is determined that the new energy power is in the first power state, and the data center allocates the corresponding new energy power to the target computing power event based on the corresponding relationship.

4. The data center computing power control method based on new energy according to claim 3 is characterized in that: The target computing power event is regulated based on the power usage strategy and the computing power allocation scheme, further comprising: If the new energy power is greater than the preset power threshold, it is determined that the available new energy power is in the second power state, and the data center allocates the corresponding new energy power to all computing power events based on the corresponding relationship.

5. The data center computing power control method based on new energy according to claim 3 is characterized in that: The target computing power event is regulated based on the power usage strategy and the computing power allocation scheme, further comprising: If the power of the new energy is 0, the data center is connected to the mains, and the target computing power event is regulated based on the event.

6. The data center computing power control method based on new energy according to claim 1 is characterized in that: Also includes: Obtaining the power generation capacity of the new energy station and the computing power of the data center; The power generation capacity is set to be higher than the computing power and the difference between the two is within a preset range.

7. A data center computing power control device based on new energy, applied to new energy sites, characterized in that: include: A setting module is used to pre-set various computing power priority levels based on urgency and importance, wherein the various computing power priority levels include: core urgent, core relatively urgent, core generally urgent, important urgent, important generally urgent, ordinary urgent, ordinary relatively urgent and ordinary generally urgent; A first acquisition and determination module is used to acquire each computing power event of the data center, and determine the corresponding target computing power priority level for each computing power event based on the computing power priority levels; A second acquisition and determination module is used to acquire the system parameters of the data center, the power generation prediction parameters of the new energy site and the power grid parameters of the current area, and determine the power consumption strategy and computing power allocation plan based on the system parameters, the power generation prediction parameters and the power grid parameters; A control module is used to obtain the processable computing power priority level included in the computing power allocation plan, traverse the various computing power events to find the target computing power event whose target computing power priority level is included in the processable computing power priority level, and control the target computing power event based on the power consumption strategy and the computing power allocation plan.

8. The data center computing power control device based on new energy according to claim 7 is characterized in that: The second acquisition and determination module includes: A sending unit, used to send the system parameter, the power generation prediction parameter and the grid parameter to a preset computing power allocation model, wherein the preset computing power allocation model is trained based on historical computing power sample data; The first acquisition unit is used to obtain the power usage strategy and the computing power allocation plan output by the preset computing power model, wherein the power usage strategy includes: available new energy power, and the computing power allocation plan includes: a priority level of processable computing power.

9. The data center computing power control device based on new energy according to claim 8, characterized in that: The control module includes: A second acquisition unit is used to acquire the available new energy power included in the power consumption strategy and the computing power required for each target computing power event, wherein there is a corresponding relationship between the available new energy power and the computing power; A comparison unit, configured to compare the available new energy power with a preset power threshold; The first determination unit is used to determine that the new energy power is in a first power state if the new energy power is less than the preset power threshold, and the data center allocates the corresponding new energy power to the target computing power event based on the corresponding relationship.

10. The data center computing power control device based on new energy according to claim 9, characterized in that: The control module also includes: The second determination unit is configured to determine that the available new energy power is in a second power state if the new energy power is greater than the preset power threshold. The data center allocates the corresponding new energy power to all computing power events based on the corresponding relationship.

11. A storage medium, characterized in that: The storage medium includes a stored program, wherein the program executes the data center computing power regulation method based on new energy as described in claims 1-6.

12. A processor, characterized in that: The processor is used to run a program, wherein the program, when running, executes the data center computing power regulation method based on new energy as described in claims 1-6.

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