CN115358859A - Energy efficiency and carbon emission calculation method and device for data center and electronic equipment - Google Patents

Energy efficiency and carbon emission calculation method and device for data center and electronic equipment Download PDF

Info

Publication number
CN115358859A
CN115358859A CN202211027486.9A CN202211027486A CN115358859A CN 115358859 A CN115358859 A CN 115358859A CN 202211027486 A CN202211027486 A CN 202211027486A CN 115358859 A CN115358859 A CN 115358859A
Authority
CN
China
Prior art keywords
energy efficiency
data center
parameters
typical value
carbon emission
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Pending
Application number
CN202211027486.9A
Other languages
Chinese (zh)
Inventor
程明
毛宏举
闫月君
王涛
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Alibaba China Co Ltd
Original Assignee
Alibaba China Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Alibaba China Co Ltd filed Critical Alibaba China Co Ltd
Priority to CN202211027486.9A priority Critical patent/CN115358859A/en
Publication of CN115358859A publication Critical patent/CN115358859A/en
Priority to PCT/CN2023/114509 priority patent/WO2024041578A1/en
Pending legal-status Critical Current

Links

Images

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q10/00—Administration; Management
    • G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
    • G06Q10/063—Operations research, analysis or management
    • G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
    • G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/26—Government or public services
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
    • Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
    • Y02P90/80—Management or planning
    • Y02P90/84—Greenhouse gas [GHG] management systems

Landscapes

  • Business, Economics & Management (AREA)
  • Human Resources & Organizations (AREA)
  • Engineering & Computer Science (AREA)
  • Strategic Management (AREA)
  • Development Economics (AREA)
  • Economics (AREA)
  • Theoretical Computer Science (AREA)
  • Tourism & Hospitality (AREA)
  • Marketing (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Educational Administration (AREA)
  • Accounting & Taxation (AREA)
  • Finance (AREA)
  • Entrepreneurship & Innovation (AREA)
  • Game Theory and Decision Science (AREA)
  • Operations Research (AREA)
  • Quality & Reliability (AREA)
  • Technology Law (AREA)
  • Health & Medical Sciences (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

The embodiment of the specification provides an energy efficiency and carbon emission reference value establishing method and device for a data center, an electronic device, a storage medium, the data center and a computer program product, wherein the energy efficiency reference value establishing method for the data center comprehensively considers three dimensions of resource use efficiency, computing power use rate, computing power energy efficiency and the like of the data center, realizes full-ring comprehensive evaluation of the data center from resource input to performance output, can scientifically and accurately reflect the energy consumption-output state of the data center, is beneficial to scientifically establishing a carbon emission reference and a free carbon emission limit of the data center, effectively guides related optimization of energy efficiency and carbon emission of the data center, and improves the performance of the data center.

Description

Energy efficiency and carbon emission calculation method and device for data center and electronic equipment
Technical Field
The present disclosure relates to energy and carbon emission management technologies in the field of computer applications, and in particular, to a method and an apparatus for calculating energy efficiency and carbon emission of a data center, an electronic device, a storage medium, a data center, and a computer program product.
Background
In 2021, 16 months 7, the national carbon emission right is traded and marketed, and carbon emission parameters (carbon emission for short) gradually become production indexes concerned by various production participants.
Internet Data centers (IDCs, hereinafter referred to as Data centers) have high energy consumption and carbon emission, and some cities have been introduced into carbon emission market at present, and may be introduced into national carbon emission markets in the future. An important link of bringing the data center into a carbon emission market is carbon emission benchmark establishment and carbon emission quota division, and a large optimization space exists in a current related system and rule, so that a calculation method for energy efficiency and carbon emission of the data center is necessary to be provided, and the method has great significance in assisting in carbon emission management of the data center and promoting green and low-carbon development of the data center.
Disclosure of Invention
The embodiment of the specification provides a method and a device for calculating energy efficiency and carbon emission of a data center and electronic equipment, so that the evaluation of the comprehensive efficiency of a full chain from energy consumption input to performance output of the data center is realized in the process of calculating the energy efficiency and carbon emission parameters of the data center, a certain guiding significance is provided for the optimization of the carbon emission parameters of the data center, and help is provided for the good development of the industry of the data center.
In order to achieve the technical purpose, the embodiments of the present specification provide the following technical solutions:
in a first aspect, an embodiment of the present disclosure provides a method for calculating energy efficiency and carbon emission of a data center, where the method for calculating energy efficiency and carbon emission of a data center includes:
acquiring energy efficiency parameters of the data center, wherein the energy efficiency parameters comprise resource use efficiency, force calculation use rate and force calculation energy efficiency;
determining respective corresponding weights of the energy efficiency parameters of the data center, and determining the comprehensive energy efficiency of the data center according to the energy efficiency parameters of the data center and the respective corresponding weights of the energy efficiency parameters, wherein the comprehensive energy efficiency is used for calculating the carbon emission of the data center.
In a second aspect, an embodiment of the present disclosure provides a method for calculating energy efficiency and carbon emission of a data center, where the method for calculating energy efficiency and carbon emission of a data center includes:
the method comprises the steps of obtaining energy efficiency parameters of a data center, wherein the energy efficiency parameters are used for representing resource use efficiency and calculation power use and output states of the data center;
and integrating energy efficiency parameters of the data center and determining the integrated energy efficiency of the data center.
In a third aspect, an embodiment of the present specification provides an energy efficiency and carbon emission computing apparatus for a data center, including:
the first energy efficiency acquisition module is used for acquiring energy efficiency parameters of the data center, wherein the energy efficiency parameters comprise resource utilization efficiency, calculated force utilization rate and calculated force energy efficiency;
the first energy efficiency determining module is used for determining respective corresponding weights of energy efficiency parameters of the data center, and determining comprehensive energy efficiency of the data center according to the energy efficiency parameters of the data center and the respective corresponding weights of the energy efficiency parameters, wherein the comprehensive energy efficiency is used for calculating carbon emission of the data center.
In a fourth aspect, embodiments of the present specification provide an energy efficiency and carbon emission computing apparatus for a data center, including:
the second energy efficiency acquisition module is used for acquiring energy efficiency parameters of the data center, and the energy efficiency parameters are used for representing the resource utilization efficiency and the computing power utilization and output states of the data center;
and the second energy efficiency determining module is used for integrating energy efficiency parameters of the data center and determining the integrated energy efficiency of the data center, and the integrated energy efficiency is used for calculating the carbon emission of the data center.
In a fifth aspect, an embodiment of the present specification provides an electronic device, including: a memory and a processor;
wherein the memory is connected with the processor and is used for storing programs;
the processor is configured to execute the program stored in the memory to implement the method for calculating energy efficiency and carbon emission in the data center according to any one of the above aspects.
In a sixth aspect, the present specification provides a storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method for calculating energy efficiency and carbon emission of a data center is implemented.
In a seventh aspect, an embodiment of the present specification further provides a data center, including: the system comprises IT equipment and accounting equipment connected with the IT equipment, wherein the accounting equipment is used for realizing the energy efficiency and carbon emission calculation method of the data center.
In an eighth aspect, embodiments of the present specification provide a computer program product or a computer program comprising computer instructions stored in a computer-readable storage medium; and a processor of the computer device reads the computer instructions from the computer readable storage medium, and when the processor executes the computer instructions, the method for calculating the energy efficiency and the carbon emission of the data center is realized.
It can be seen from the foregoing technical solutions that, in the energy efficiency and carbon emission calculation method for a data center, a device, an electronic device, a storage medium, a data center, and a computer program product are provided in the embodiments of the present specification, in the determination process of a carbon emission parameter, the energy efficiency and carbon emission calculation method for a data center comprehensively considers resource usage efficiency, computational power usage, and output state as energy efficiency parameters, implements a full-chain comprehensive efficiency evaluation system for energy input and performance output of the data center, gives consideration to resource efficiency, computational power, and computational efficiency of the data center, comprehensively reflects a comprehensive efficiency level of the data center, overcomes a problem that a traditional carbon emission quota determination method cannot reflect a full-circle comprehensive efficiency of energy utilization and computational power output of the data center, gives a certain guiding significance to optimization of a carbon emission parameter of the data center, and provides help for good development of a data center industry.
Drawings
In order to more clearly illustrate the embodiments of the present specification or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only the embodiments of the present specification, and for those skilled in the art, other drawings can be obtained according to the provided drawings without creative efforts.
FIG. 1 is a schematic diagram of an example scenario provided by an embodiment of the present description;
FIG. 2 is a schematic flow chart diagram illustrating a method for energy efficiency and carbon emissions calculation in a data center according to an embodiment of the present disclosure;
FIG. 3 is a schematic flow chart diagram illustrating a method for energy efficiency and carbon emissions calculation in a data center according to another embodiment of the present disclosure;
FIG. 4 is a schematic flow chart diagram illustrating a method for energy efficiency and carbon emissions calculation in a data center according to yet another embodiment of the present disclosure;
FIG. 5 is a schematic flow chart diagram illustrating a method for energy efficiency and carbon emissions calculation in a data center according to yet another embodiment of the present disclosure;
FIG. 6 is a schematic flow chart diagram illustrating a method for energy efficiency and carbon emissions calculation in a data center according to an alternative embodiment of the present disclosure;
FIG. 7 is a schematic flow chart diagram illustrating a method for energy efficiency and carbon emissions calculation in a data center according to another alternative embodiment of the present disclosure;
FIG. 8 is a schematic diagram illustrating an interface for displaying an energy efficiency optimization report according to an embodiment of the present disclosure;
FIG. 9 is a schematic diagram illustrating an interface for displaying an energy efficiency optimization report according to another embodiment of the present disclosure;
FIG. 10 is a schematic flow chart diagram illustrating a method for energy efficiency and carbon emissions calculation in a data center according to yet another alternative embodiment of the present disclosure;
FIG. 11 is a schematic diagram of an energy efficiency and carbon emissions computing device of a data center according to an embodiment of the present disclosure;
FIG. 12 is a schematic diagram of an energy efficiency and carbon emissions computing device for a data center according to another embodiment of the present disclosure;
fig. 13 is a schematic structural diagram of a data center provided in an embodiment of the present specification;
fig. 14 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
Unless otherwise defined, technical or scientific terms used in the embodiments of the present specification should have the ordinary meaning as understood by those having ordinary skill in the art to which the specification pertains. The terms "first," "second," and the like, as used in the embodiments of the present description, do not denote any order, quantity, or importance, but rather are used to avoid mixing of the constituent elements.
Unless the context requires otherwise, throughout the specification, "a plurality" means "at least two" and "includes" are to be interpreted in an open, inclusive sense, i.e., as "including, but not limited to". In the description of the specification, the terms "one embodiment," "some embodiments," "an example embodiment," "an example," "a specific example" or "some examples" or the like are intended to indicate that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the specification. The schematic representations of the above terms are not necessarily referring to the same embodiment or example.
The technical solutions in the embodiments of the present specification will be clearly and completely described below with reference to the drawings in the embodiments of the present specification, and it is obvious that the described embodiments are only a part of the embodiments of the present specification, and not all of the embodiments. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments in the present specification without making any creative effort belong to the protection scope of the present specification.
The data center is used as an entity for mass data storage, operation and interaction, comprises equipment such as a computer, refrigeration, power supply, illumination and machinery, is a data center and a calculation carrier of technologies such as 5G, artificial Intelligence (AI), the Internet of things and cloud calculation, and is an important support for development of new infrastructure.
The server cluster and the auxiliary cooling system included in the data center are high-energy-consumption devices which are highly dependent on electric power to operate uninterruptedly. According to the display of white paper book in data center (2022), published by the institute of information and communications in china at 2022, 4 months: in 2021, the energy consumption of the national data center is about 2166 hundred million kilowatt hours, which accounts for 2.6% of the total electricity consumption in the country, and the emission of indirect greenhouse gases generated by electricity consumption reaches about 1.35 million tons, which accounts for about 1.14% of the carbon emission in the country. In the last decade, the whole electricity consumption of the data center industry in China is increased year by year at a speed of exceeding 10 percent year by year. As overall energy demand increases, data center energy consumption issues are of high concern. In order to promote the carbon consumption reduction of the data center, the state intends to bring the data center into the national unified carbon market, so that the emission data monitoring, reporting and checking are promoted, the industry energy efficiency standard implementation is promoted, and the minimization of the industry total emission reduction cost is realized by means of a market mechanism.
Therefore, in the background of industry development that a data center is about to be brought into a carbon emission market, how to perform accurate and reasonable energy efficiency and carbon emission accounting on the data center becomes a problem to be solved urgently in order to solve key problems of carbon emission allocation and the like in mechanism design of the carbon emission market brought into the data center. Accurate and reasonable energy efficiency and carbon emission accounting can provide carbon emission reference for data center industry professional enterprises, guide the enterprises to optimize equipment emission, and improve the scientificity of the data center industry carbon emission reference value and the carbon emission matching and distributing process.
In an example scenario of the present specification, referring to fig. 1, energy consumption and carbon emission generated by a data center during a working process are currently generally evaluated by using a utilization efficiency (Usage efficiency) index, where resource Usage measures related to the utilization efficiency index mainly include: PUE (Power Use Efficiency), WUE (Water Use Efficiency), CUE (Carbon Use Efficiency), IUE (Infrastructure Use Efficiency), and gu (resource Efficiency), etc. A more commonly used PUE is described below:
PUE＝P total/ P IT (1)
wherein, P total The method is characterized in that the method refers to the total power consumption of a data center in kilowatt-hour;
P IT IT refers to the power consumption of IT (Information Technology) equipment in a data center, and the unit is kilowatt-hour.
The IT equipment is basic equipment for the output power of the data center and can comprise a server, a storage device, network equipment and the like.
In addition, the reciprocal of the PUE is called data center infrastructure efficiency DCiE =1/PUE, DCiE reflects the proportion of IT equipment in the total energy efficiency of the data center, and the value is smaller than 1, and the closer to 1, the better.
Derived efficiencies of PUEs include pPUE (partial power usage efficiency), dPUE (design power usage efficiency) and iPUE (period power usage efficiency). Wherein dPUE is an expected PUE determined by a data center design target, and iPEE refers to the PUE measured at a specified time, and is not a full-year value.
pPUE＝P total_sub /P IT_sub (2)
Wherein, P total_sub The total power consumption in a subsystem (a power distribution system, network equipment, a cooling system and the like) of the data center is unit kilowatt-hour.
P IT_sub IT refers to the power consumption of IT equipment in a data center in kilowatt-hour.
Besides, the domestic relevant standards for energy consumption assessment of data centers include: EEUE-R (measured value of Electric Energy Usage efficiency), EEUE-X (corrected value of Electric Energy Usage efficiency), WUE (Water Usage efficiency, water resource utilization efficiency), CUE (Carbon Usage efficiency, carbon utilization efficiency), IUE (Infrastructure Usage efficiency, infrastructure utilization rate), gu (Grid Usage efficiency, resource efficiency), REF (Renewable Energy Factor, renewable Energy utilization rate), ERF (Energy reuse Factor), and seu (Storage Energy Usage Ratio).
The indexes are focused on the consumption, conversion and utilization structure analysis of power resources, water resources and the like of the data center, and besides the PUE, most of the indexes are complex in calculation and difficult to be widely accepted. Moreover, the above indexes cannot reflect the calculation power output condition supported by the data center in the resource consumption process, cannot cover the full chain of energy conversion and application of the data center, and cannot provide the full view insight of the comprehensive efficiency of the data center.
In view of this, the embodiment of the present specification provides a method for calculating energy efficiency and carbon emission of a data center, which comprehensively considers resource usage efficiency and computational power usage and output states as energy efficiency parameters in a determination process of comprehensive energy efficiency, so as to implement a full-chain comprehensive efficiency evaluation system for energy consumption input and performance output of the data center, give consideration to resource efficiency, computational power and computational efficiency of the data center, comprehensively reflect a comprehensive efficiency grade of the data center, overcome a problem that a traditional carbon emission quota determination method cannot reflect full-ring comprehensive efficiency of energy utilization and computational power output of the data center, give a certain guiding significance to optimization of a data center energy efficiency reference value, and provide help for good development of a data center industry.
In addition, the energy efficiency calculation method also determines respective corresponding weights for the energy efficiency parameters of the data center according to the attributes of the data center, so that the corresponding energy efficiency parameter weights can be determined according to different attributes of the data center in the determination process of the energy efficiency reference value of the data center, a foundation is laid for the determination of the targeted energy efficiency reference value of the data center with different attributes, and the energy efficiency of the data center and the pertinence of the carbon emission calculation method are improved.
The energy efficiency and carbon emission calculation method of the data center provided by the embodiment of the specification is described below with reference to possible exemplary embodiments.
An exemplary embodiment of the present specification provides a method for calculating energy efficiency and carbon emission of a data center, as shown in fig. 2, including:
s101: and acquiring energy efficiency parameters of the data center, wherein the energy efficiency parameters are used for representing the resource use efficiency and the calculated power use and output states of the data center.
In step S101, in addition to the resource usage efficiency, the computational power usage and output state is used as a part of the energy efficiency parameter, that is, in the process of evaluating the comprehensive energy efficiency of the data center, not only the energy consumption of the data center is considered, but also the computational power output supported by the energy consumption is considered, so that the energy efficiency parameter for determining the comprehensive energy efficiency covers a full-ring from the energy utilization to the performance output, the comprehensive energy efficiency of the data center is considered in multiple dimensions, the determination of the comprehensive energy efficiency comprehensively reflects the comprehensive energy efficiency level of the data center, and the problem that the existing comprehensive energy efficiency determination method cannot comprehensively reflect the full-ring comprehensive efficiency of the energy utilization and computational power output of the data center is effectively overcome.
In one embodiment of the present specification, "resource" in the resource utilization efficiency refers to a resource used by the data center, and the resource used by the data center includes at least one of energy, water resource, cooling resource, and space resource occupied by the U bit of the rack. The water resource may include water used by the data center for server cooling, machine room humidification, and the like, the cooling resource may include cooling liquid used by the data center except for cooling water, and the energy in the resource used by the data center includes, but is not limited to, at least one of energy forms of electric energy, light energy, heat energy, and the like. Accordingly, the resource utilization efficiency refers to the utilization efficiency of resources used by the data center. Alternatively, taking the electric energy used by the data center as an example, the resource utilization efficiency may be the PUE described above, or may also be an index reflecting the electric energy utilization efficiency, such as the pPUE (partial electric energy utilization efficiency), the dPUE (designed electric energy utilization efficiency), or the iPUE (period electric energy utilization efficiency).
The parameters for characterizing the calculated power usage and the output state may be the calculated power usage rate and the calculated power efficiency of the data center, or may be parameters after further processing (such as normalization, standardization, etc.) based on the calculated power usage rate and the calculated power efficiency, which is not limited in this specification. In the data center, the IT equipment is divided into computing, storage and network equipment, wherein the Energy consumption of the computing part is the largest and occupies more than 90% of the total Energy consumption of the IT equipment, so that the Computational Energy Efficiency (CEUE) representing the Energy consumption Efficiency of the computing part can evaluate the Energy Efficiency of the data center from the Computational Energy Efficiency dimension of the data center.
For the calculated power utilization rate, the average utilization rate of the calculated power in a specific time of the data center can be used as a representation value of the calculated power utilization rate, the average idle rate of the calculated power in a specific time of the data center can be used as a representation value of the calculated power utilization rate, and the calculated power can be the calculated power for realizing the output of a target result by processing information data. In a data center, computing power may be represented in terms of the CPU (processor) resources of the server. The computing power usage rate may evaluate the energy efficiency of the data center from the data center computing power usage dimension. That is, when the representation value of the computing power utilization rate indicates the average utilization rate of the computing power in a specific time of the data center, the average utilization rate eta of the server CPU of the data center in the specific time can be used CPU Expressed in unit%, may be specifically expressed as:
η CPU ＝CPU _U /CPU _tot (3)
wherein, the CPU _U Refers to the used CPU resource, unit Hz, CPU _tot Refers to the total CPU resources in Hz. When the characteristic value of the computing power utilization rate indicates an average idle rate of the computing power in a specific time of the data center, the characteristic value of the computing power utilization rate can be expressed as: 1-. Eta. CPU 。
S102: and integrating energy efficiency parameters of the data center, and determining the integrated energy efficiency of the data center, wherein the integrated energy efficiency is used for calculating the carbon emission of the data center.
In step S102, the comprehensive energy efficiency is determined by comprehensively considering three dimensions, such as the resource utilization efficiency, the computational power utilization rate, and the computational power efficiency of the data center, so that a full-link multi-dimensional comprehensive evaluation from energy utilization to performance output of the data center is realized, the determined comprehensive energy efficiency more scientifically and accurately reflects the energy efficiency-output state of the data center, and a solid foundation is laid for scientifically establishing a carbon emission standard and a free carbon emission limit of the data center.
When the energy efficiency parameters of the comprehensive data center are used for determining comprehensive energy efficiency, the energy efficiency parameters may be directly superposed, weights may be distributed to the energy efficiency parameters and then added, or the energy efficiency parameters may be obtained by calculating according to a preset formula, which is not limited in this specification and is determined according to actual conditions.
In addition, the scientific and accurate comprehensive energy efficiency can also guide the data center to optimize the energy efficiency, and contributes to energy conservation, emission reduction and energy efficiency improvement of the data center.
Since the comprehensive energy efficiency of the data center is associated with the carbon emission of the data center, after the comprehensive energy efficiency of the data center is determined, the carbon emission of the data center can be calculated based on the comprehensive energy efficiency.
For data centers with different attributes, the weight of each energy efficiency parameter may be different, and in order to accurately account for the energy efficiency and the carbon emission of the data centers with different attributes, an exemplary embodiment of the present specification provides another method for calculating the energy efficiency and the carbon emission of a data center, as shown in fig. 3, including:
s201: and acquiring energy efficiency parameters of the data center, wherein the energy efficiency parameters comprise resource utilization efficiency, computing power utilization rate and computing power efficiency.
In step S201, the calculation power usage rate and the calculation power efficiency are used as parameters for representing the calculation power usage and the output state. The computing power efficiency may be obtained by computing a computing power efficiency representing an energy efficiency of a computing power portion of the IT device, or may be obtained by computing a parameter representing an energy efficiency of a storage portion or a network portion of the IT device, which is not limited in this specification.
The computing efficiency may be characterized by the computing efficiency itself, or by a parameter obtained by normalizing the computing efficiency, for example, the computing efficiency may be expressed as:
η CEUE = (CEUE actual value-CEUE reference value)/CEUE reference value (4)
The CEUE indexes the IT equipment power consumption required by the unit calculation power of the data center, and the unit is W/TFLOPS. The calculation formula refers to formula (5):
CEUE＝P IT /CP (5)
wherein, P IT The calculation method is characterized in that the calculation method refers to total Power of IT equipment, and the unit kW and CP refer to calculation Power of a data center and the unit FLOPS (Floating-point Operations Per Second) are used for evaluating general calculation Power and high-performance calculation Power of the data center. The CEUE reference value can be determined by the national data center overall calculation capability value published recently or the average value of the national data center overall calculation capability values published within the last two years.
S202: determining respective weights corresponding to the energy efficiency parameters of the data center, and determining comprehensive energy efficiency of the data center according to the energy efficiency parameters of the data center and the respective weights corresponding to the energy efficiency parameters, wherein the comprehensive energy efficiency is used for calculating carbon emission of the data center.
After the weights corresponding to the energy efficiency parameters are determined, the sum of the products of the energy efficiency parameters of the data center and the corresponding weights can be used as the comprehensive energy efficiency of the data center. Because the characterization modes of the energy efficiency parameters of the data center can be various, more specifically, the sum of the products of the respective characterization values of the resource utilization efficiency, the calculation power efficiency and the calculation power utilization and the respective corresponding weights can be used as the comprehensive energy efficiency of the data center. If the electric energy utilization efficiency PUE is adopted as the representation value of the resource utilization efficiency, the representation value of the calculated power utilization rate is 1-eta CPU Expressing, using the computing power efficiency eta of IT equipment CEUE As a representative value of the calculation power efficiency, the comprehensive energy efficiency can be calculated according to the following formula (6):
S tot ＝k1·(PUE)+k2·(1-η CPU )+k3·η CEUE (6)
wherein S is tot Representing the overall energy efficiency, PUE the efficiency of use of electric energy, eta CPU Mean usage, η, of computing power in a particular time of a data center CEUE Representing IT equipmentThe calculation of the energy efficiency. k1 represents a weight corresponding to resource utilization efficiency (electric energy utilization efficiency in this embodiment), k2 represents a weight corresponding to a characteristic value of the computing power utilization rate, and k3 represents a weight corresponding to the computing power efficiency (computing power efficiency of the IT device in this embodiment).
Optionally, the determining the weight corresponding to each energy efficiency parameter of the data center includes:
s2021: and determining weights corresponding to the energy efficiency parameters of the data center according to the attributes of the data center, wherein the attributes of the data center are used for representing the type, the operating environment and the operating state of the data center.
As described above, because the attributes of the data centers are different, the contribution degrees of the resource usage efficiency, the computing power usage rate, and the computing power efficiency to the overall energy efficiency of the data center are also different, and therefore, the weights corresponding to the energy efficiency parameters of the data center need to be determined according to the attributes of the data centers.
The types of the data centers include, but are not limited to, ultra-large data centers, medium data centers and small data centers classified according to scale, enterprise-owned data centers, third party hosted data centers classified according to operation, class a data centers, class B data centers and class C data centers classified according to the GB50174-2008 standard.
The operating environment of the data center may include the area where the data center is located, the current season, etc., and in some embodiments, the operating environment of the data center may also include incentives for the area where the data center is located.
The operation state of the data center includes but is not limited to the purpose of the data center and the kind of machine room. Uses of the data center include, but are not limited to, data storage, data processing analysis, and product services.
When the attributes of the data centers are different, the contribution of each energy efficiency parameter to the comprehensive energy efficiency is different. For example, if data center 1 and data center 2 are distributed in city a and city B, respectively, and city a has power shortage, power usage is allocated from other cities throughout the year. Resources such as water, wind, solar energy and the like in the city B are rich, the matching hydropower station, wind power station and solar power station are perfect, various power stations can not only meet the power consumption of the city, but also can transmit a large amount of power to other cities, so under the condition, the weight of the resource use efficiency of the data center 1 in the city A can be larger than the resource use efficiency of the data center 2 in the city B, and the resource and cost (such as power transmission cost) required to be consumed when the data center 1 uses one-degree power are larger than the resource and cost required to be consumed when the data center 2 uses one-degree power.
For example, the data center 3 is located in a northern city C, which is very cold in winter and needs to consume a large amount of power, firepower and other resources to meet the heating demand, and the city C is pleasant in summer climate and does not need to meet the power demand of refrigeration equipment such as air conditioners like other cities. The resource usage efficiency weight of the data center 3 in winter may be greater than the resource usage efficiency weight in summer. The specification does not exhaust all kinds of conditions, and the weight determination of all kinds of energy efficiency parameters is determined according to actual conditions.
After establishing a comprehensive energy efficiency determination mode similar to that shown in formula (6), a data center comprehensive performance evaluation system may be established based on the determination mode, and specifically, as shown in fig. 4, the method for calculating energy efficiency and carbon emission of a data center further includes:
s301: acquiring a first typical value, a second typical value and a third typical value which respectively correspond to the energy efficiency parameters, wherein the first typical value represents a typical value when the corresponding energy efficiency parameter is in a first energy efficiency interval, the second typical value represents a typical value when the corresponding energy efficiency parameter is in a second energy efficiency interval, and the third typical value represents a typical value when the corresponding energy efficiency parameter is in a third energy efficiency interval; and when the energy efficiency parameters are in the first energy efficiency interval, the second energy efficiency interval and the third energy efficiency interval, the represented energy efficiency is reduced in sequence.
The first typical value, the second typical value, and the third typical value refer to typical values of data centers in which energy efficiency parameters are in an advanced interval (i.e., a first energy efficiency interval, which may be regarded as a high energy efficiency interval), a general interval (i.e., a second energy efficiency interval, which may be regarded as a general energy efficiency interval), and a lagging interval (i.e., a third energy efficiency interval, which may be regarded as a low energy efficiency interval), where the typical values may be median or average of the data centers in the data center industry in the foregoing intervals, and this specification does not limit this.
Referring to table 1, table 1 shows a first typical value, a second typical value, and a third typical value for each of a feasible PUE, an computational usage rate, and a computational efficiency.
TABLE 1 typical values of energy efficiency parameters for data centers
Figure BDA0003816317610000101
S302: and taking the sum of the products of the first typical value corresponding to each energy efficiency parameter and the weight corresponding to each energy efficiency parameter as a first energy efficiency typical value.
Taking the first typical value illustrated in table 1 as an example, taking k1=50, k2=100, and k3=50 in equation (6) as an example, the first energy efficiency typical value =1.2 × 50+100 × 30% + (-0.6) × 50=60.
S303: and taking the sum of the products of the second typical value corresponding to each energy efficiency parameter and the weight corresponding to each energy efficiency parameter as a second energy efficiency typical value.
Taking the second typical value illustrated in table 1 as an example, taking k1=50, k2=100, and k3=50 in equation (6) as an example, the second energy efficiency typical value =1.4 × 50+100 × 70% +0 × 50=140.
S304: and taking the sum of the products of the third typical value corresponding to each energy efficiency parameter and the weight corresponding to each energy efficiency parameter as a third energy efficiency typical value.
Taking the third exemplary value illustrated in table 1 as an example, taking k1=50, k2=100, and k3=50 in equation (6) as an example, the third energy efficiency exemplary value =1.8 × 50+100 × 90% +0.6 × 50=210.
Still referring to table 1, typical values of energy efficiency obtained by calculation based on the obtained energy efficiency parameters are also shown in table 1 t 。
As will be readily understoodIs, S tot The smaller, the better the resource utilization and computational yield characterizing a data center.
S305: a first critical value is determined between the first energy efficiency typical value and the second energy efficiency typical value.
S306: and determining a second critical value between the second energy efficiency typical value and the third energy efficiency typical value.
S307: and determining an energy efficiency state of the data center according to the magnitude relation between the comprehensive energy efficiency of the data center and the first critical value and the second critical value, wherein the energy efficiency state is used for representing the excellent grade of the comprehensive energy efficiency of the data center.
The first critical value may be between the first energy efficiency typical value and the second energy efficiency typical value as a boundary for distinguishing a good level and a good level of the comprehensive energy efficiency of the data center, and the second critical value may be between the second energy efficiency typical value and the third energy efficiency typical value as a boundary for distinguishing a good level and a poor level of the comprehensive energy efficiency of the data center.
Referring to table 2, table 2 shows one possible data center overall performance ranking system. In table 2, the first critical value is an average (e.g., 100) of the first energy efficiency typical value (e.g., 60) and the second energy efficiency typical value (e.g., 140), and the second critical value is an average (e.g., 190) of the second energy efficiency typical value (e.g., 140) and the third energy efficiency typical value (e.g., 210).
TABLE 2 data center comprehensive performance grading system
Figure BDA0003816317610000111
In combination with table 2, it can be found that, after the first critical value and the second critical value are determined, the energy efficiency state of the data center, which represents the excellent level of carbon emission of the data center, can be evaluated according to the magnitude relationship between the integrated energy efficiency of the data center and the first critical value and the second critical value. Still taking table 2 as an example, when the comprehensive energy efficiency of the data center is less than or equal to the first critical value, the comprehensive energy efficiency of the data center can be considered to be in an excellent level, and the energy efficiency and the computing power output condition of the data center are characterized to be excellent. When the comprehensive energy efficiency of the data center is greater than the first critical value and less than or equal to the second critical value, the comprehensive energy efficiency of the data center can be considered to be in a good grade, and the energy efficiency and computing power output conditions of the data center are represented to be good. When the comprehensive energy efficiency of the data center is greater than the second critical value, the comprehensive energy efficiency of the data center can be considered to be in a poor grade, the energy efficiency and the computing power output condition of the data center are represented to be poor, and the energy efficiency of the data center needs to be optimized so as to improve the comprehensive energy efficiency.
Of course, in table 2, when the integrated energy efficiency of the data center is equal to the first critical value, the superior grade of the integrated energy efficiency of the data center is classified as excellent, and when the integrated energy efficiency of the data center is equal to the second critical value, the superior grade of the integrated energy efficiency of the data center is classified as good. In some embodiments, the fine ranking of the integrated energy efficiency of the data center may also be classified as good when the integrated energy efficiency of the data center is equal to the first threshold. Similarly, when the integrated energy efficiency of the data center is equal to the second critical value, the good level of the integrated energy efficiency of the data center may also be classified as poor, which is not limited in this specification, depending on the actual situation.
In addition to evaluating the energy efficiency state of the data center according to the magnitude relationship between the integrated energy efficiency of the data center and the first and second critical values, referring to fig. 5, the energy efficiency and carbon emission calculation method of the data center further includes:
s401: and determining an energy efficiency reference value of the data center according to the first critical value and the second critical value, and determining a carbon emission reference value of the data center according to the energy efficiency reference value of the data center.
After the demarcation points (namely the first critical value and the second critical value) of the excellent levels of the comprehensive energy efficiency of the data center are determined, an energy efficiency reference value representing the energy efficiency level of the mainstream data center can be determined according to the critical values, and a carbon emission reference value can be further determined according to the energy efficiency reference value, and the data center can be promoted to be included into the carbon emission market according to the carbon emission reference value which can be used as the determination basis of the free carbon emission credit.
Alternatively, the energy efficiency reference value may be between the first threshold and the second threshold, i.e., the energy efficiency reference value is greater than the first threshold and less than the second threshold. The energy efficiency reference value may also be equal to an average of the sum of the first and second threshold values. Taking the first threshold value as 100 and the second threshold value as 190 as an example, the energy efficiency reference value is greater than 100 and less than 190, which may be used to characterize the carbon emission level of the mainstream data center, and of course, the energy efficiency reference value may be determined as an average of the sum of 100 and 190 (i.e. 145), or may be determined closer to the second threshold value (e.g. 150 or 155 or 160, etc.), so that the annual energy efficiency reference value of more data centers may be within the free carbon emission limit, so as to encourage the development of the data center industry.
The data center carbon emission reference value can also be obtained according to the data center energy efficiency reference value mapping, and for example, the data center carbon emission reference value can be in a direct proportion relationship.
As described above, the first typical value, the second typical value, and the third typical value corresponding to each energy efficiency parameter in table 1 may change as the industry of the data center continues to develop, and therefore, in an embodiment of the present specification, referring to fig. 6, the method for calculating energy efficiency and carbon emission of the data center further includes:
s501: and updating the first typical value, the second typical value and the third typical value corresponding to the energy efficiency parameters at preset intervals, and returning the sum of the products of the first typical value corresponding to each energy efficiency parameter and the weight corresponding to each energy efficiency parameter as a first energy efficiency typical value.
The first typical value, the second typical value and the third typical value corresponding to each energy efficiency parameter are updated every other preset time, so that the comprehensive energy efficiency and carbon emission accounting of the data center is closer to the current development situation of the data center industry and follows the industry development, and the comprehensive energy efficiency and carbon emission accounting is more scientific and accurate.
The preset time may be 6 months, one year, two years, etc., and the preset time may be selected according to the development speed of the data center industry, which is not limited in this specification.
In addition, in the process of determining the comprehensive energy efficiency of the data center, the magnitude relation between the product of each energy efficiency parameter of the data center and the corresponding weight and the first energy efficiency typical value, the second energy efficiency typical value and the third energy efficiency typical value can also guide the optimization direction of the comprehensive energy efficiency of the data center, and the optimization direction can be embodied in the form of an energy efficiency optimization report.
Specifically, referring to fig. 7, the energy efficiency and carbon emission calculation method for data update further includes:
s601: and generating an energy efficiency optimization report according to the energy efficiency parameter of the data center and the size relationship of the first typical value, the second typical value and the third typical value corresponding to the energy efficiency parameter.
Still taking Table 1 as an example, assume that resource utilization efficiency is characterized by PUE and that the characterization value of computational power utilization is 1- η CPU Characterization, calculation of force-energy efficiency by η CEUE (the calculation method may refer to equation (4)), the first, second, and third typical values of PUE may be 1.2, 1.4, and 1.8, respectively, the first, second, and third typical values of the characterization value of the calculation power usage rate may be 30%, 70%, and 90%, respectively, and the first, second, and third typical values of the calculation power efficiency may be 1.2, 1.4, and 1.8, respectively.
Accordingly, assuming that the measured PUE of the data center α is 1.9, the characteristic value of the computational utilization rate is 20%, and the computational efficiency is 1.3, it can be found that the PUE of the data center α is poor, and the characteristic value of the computational utilization rate and the computational efficiency are excellent by comparing the PUE with the first typical value, the second typical value and the third typical value corresponding to the above, and referring to fig. 8, the PUE of the data center α can be indicated in the energy efficiency optimization report, and it is suggested that the PUE is optimized (the optimization includes, but not limited to, the cooling manner of the data center, and the like, which is not limited by the present specification) to improve the energy efficiency integration of the data center α.
Assuming a measured PUE of 1.4 for data center β, a characteristic value of computing power usage was 85%, and computing power efficiency was 1.9. Comparing the representation values of the PUE and the calculation utilization rate and the calculation efficiency with the corresponding first typical value, second typical value and third typical value, it can be found that the calculation utilization rate and the calculation efficiency of the data center beta are poor, and the PUE is excellent, referring to FIG. 9, the calculation utilization rate and the calculation efficiency of the data center beta can be shown in an energy efficiency optimization report, and the calculation efficiency of the data center beta are recommended to be optimized, so that the comprehensive energy efficiency of the data center beta is improved.
The embodiment of the present specification further illustrates a feasible obtaining manner of the energy efficiency parameter, and optionally, referring to fig. 10, the energy efficiency and carbon emission calculation method of the data center includes:
s901: and acquiring the operation parameters of the data center, wherein the operation parameters are used for representing the resources used by the data center, the calculation force using state and the calculation force generated by the data center.
S902: and calculating the energy efficiency parameter of the data center according to the operation parameter.
S903: and determining weights corresponding to the energy efficiency parameters of the data center according to the attributes of the data center, wherein the attributes of the data center are used for representing the type, the operating environment and the operating state of the data center.
S904: and determining the comprehensive energy efficiency of the data center according to the energy efficiency parameters of the data center and the respective corresponding weights of the energy efficiency parameters.
Wherein, step S901 may specifically include:
s9011: and acquiring the total power consumption of the data center, the power consumption of the IT equipment, the total processor resources of the data center, the used processor resources of the data center, the total power of the IT equipment and the computing power of the data center.
Wherein, the total power consumption of the data center can be as total power P total In kilowatt-hour, corresponding ITThe power consumption of the equipment can be equal to the power P of the IT equipment of the data center IT Expressed in kilowatt-hours. Of course, in some embodiments, the total power consumption of the data center may also be the actual total power consumption Q total The unit of (A) indicates that the power consumption of the IT equipment can be equal to the power consumption Q of the IT equipment of the data center IT Expressed in kilowatts.
The total processor resources of the data center may be the master frequency (clock frequency) of the CPU \ tot Expressed in hertz (Hz). Accordingly, the used processor resources of the data center may be in the used primary frequency of the CPU U Expressed in hertz (Hz).
The data centric algorithm may be expressed in units of FLOPS in terms of the number of floating point operations performed per second.
Step S902 may specifically include:
s9021: and taking the ratio of the power consumption of the IT equipment to the total power consumption of the data center as the resource utilization efficiency of the data center.
When the resource utilization efficiency is expressed by PUE, the power consumption of the IT equipment is expressed by the power P of the IT equipment of the data center IT Representing the total power consumption of the data center in total power P total When expressed in (3), step S9021 may be expressed by equation (7).
PUE＝P total /P IT (7)
S9022: and taking the ratio of the difference value of the total processor resources of the data center and the used processor resources to the total processor resources of the data center as a representation value of the computing power utilization rate of the data center.
Step S9022 may be expressed by equation (8).
1-η CPU ＝(CPU_ tot -CPU_ U )/CPU_ tot (8)
S9023: and taking the ratio of the total power of the IT equipment to the computing power of the data center as the computing power energy efficiency of the data center, and taking the ratio of the difference value between the computing power energy efficiency of the data center and the reference computing power energy efficiency in the reference computing power energy efficiency as the computing power energy efficiency of the data center.
Step S9023 may be expressed by equations (9) and (10).
η CEUE = (CEUE actual value-CEUE reference value)/CEUE reference value (9)
CEUE actual value = P IT /CP (10)
Wherein eta is CEUE And the CEUE actual value represents the computational power efficiency, and the CEUE reference value represents the reference computational power efficiency. The benchmark computing power efficiency can be determined by the recently published national data center total computing power value calculation.
The energy efficiency parameter of the data center is calculated based on the method, and the method has the advantages of being simple and convenient in calculation method, convenient in measurement and statistics of each parameter, beneficial to simplifying the energy efficiency and carbon emission calculation method of the data center and improving the execution efficiency of the method.
Referring to fig. 11, in correspondence to the energy efficiency and carbon emission calculation method of the data center, an embodiment of the present specification further provides an energy efficiency and carbon emission calculation apparatus of a data center, including:
a first energy efficiency obtaining module 100, configured to obtain energy efficiency parameters of the data center, where the energy efficiency parameters include resource utilization efficiency, computational power utilization rate, and computational power-energy efficiency;
the first energy efficiency determining module 200 is configured to determine respective weights corresponding to energy efficiency parameters of the data center, and determine a comprehensive energy efficiency of the data center according to the energy efficiency parameters of the data center and the respective weights corresponding to the energy efficiency parameters, where the comprehensive energy efficiency is used to calculate carbon emission of the data center.
Referring to fig. 12, in correspondence to the energy efficiency and carbon emission calculation method of the data center, an embodiment of the present specification further provides another energy efficiency and carbon emission calculation apparatus of a data center, including:
a second energy efficiency obtaining module 300, configured to obtain energy efficiency parameters of a data center, where the energy efficiency parameters are used to represent resource usage efficiency and computational power usage and output states of the data center, and the computational power usage and output states are used to represent computational power usage rate and computational power efficiency of the data center;
and a second energy efficiency determining module 400, configured to synthesize energy efficiency parameters of the data center, and determine the synthesized energy efficiency of the data center, where the synthesized energy efficiency is used to calculate carbon emission of the data center.
The energy efficiency and carbon emission calculation apparatus for a data center provided in this embodiment belongs to the same application concept as the energy efficiency and carbon emission calculation method for a data center provided in the foregoing embodiment of the present application, can execute the energy efficiency and carbon emission calculation method for a data center provided in any of the foregoing embodiments of the present application, and has functional modules and beneficial effects corresponding to the execution of the energy efficiency and carbon emission calculation method for a data center. For details of the technology that is not elaborated in this embodiment, reference may be made to specific processing contents of the energy efficiency and carbon emission calculation method of the data center provided in the foregoing embodiment of the present application, and details are not described here again.
Accordingly, an exemplary embodiment of the present specification further provides a data center, as shown in fig. 13, including: the system comprises IT equipment and accounting equipment 30 connected with the IT equipment, wherein the accounting equipment 30 is used for realizing the energy efficiency and carbon emission calculation method of the data center according to any one of the above embodiments.
In an actual data center, the number of IT devices is usually multiple, the IT devices may include the server device 10 and the like, and the server device 10 and the switch 20 may be connected by an active optical cable.
In fig. 13, in addition to the server device 10 and the switch 20, a router is shown, and the switch 20 and the router are each one of network switching devices. These network switching devices may be interconnected and server devices 10 in the data center may be interconnected through these network switching devices.
The architecture shown in fig. 13 may also be referred to as a data center network, and in such a network structure, the architecture may be divided into a server layer, an Edge Switch (Edge Switch) layer, an aggregation Switch (Aggregate Switch) layer, a Core Switch (Core Switch) layer, a router layer, and an optical signal transmission layer. The active optical cable is mainly used for realizing optical communication connection between the server and the switch in the server layer.
Regarding the accounting device provided in this embodiment, the accounting device and the energy efficiency and carbon emission calculation method of the data center provided in the foregoing embodiments of the present application belong to the same application concept, and can execute the energy efficiency and carbon emission calculation method of the data center provided in any of the foregoing embodiments of the present application, and have functional modules and beneficial effects corresponding to the execution of the energy efficiency and carbon emission calculation method of the data center. For details of the technology that are not elaborately described in this embodiment, reference may be made to specific processing contents of the method for calculating energy efficiency and carbon emission in a data center provided in the foregoing embodiment of the present application, and details are not repeated here.
Another embodiment of the present application further provides an electronic device, and referring to fig. 14, an exemplary embodiment of the present specification further provides an electronic device including: the energy efficiency and carbon emission calculation method of the data center according to various embodiments of the present specification described in the above embodiments of the present specification is implemented by a processor, and the processor is used for executing the computer program.
The internal structure of the electronic apparatus may be as shown in fig. 14, and the electronic apparatus includes a processor, a memory, a network interface, and an input device connected through a system bus. Wherein the processor of the electronic device is configured to provide computing and control capabilities. The memory of the central control device comprises a nonvolatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operating system and the computer program to run on the non-volatile storage medium. The network interface of the electronic device is used for connecting and communicating with an external terminal through a network. The computer program is executed by a processor to perform the steps of the energy efficiency and carbon emission calculation method of the data center according to various embodiments of the present description described in the above embodiments of the present description.
The processor may include a main processor and may also include a baseband chip, modem, and the like.
The memory stores programs for executing the technical scheme of the invention and also stores an operating system and other key services. In particular, the program may include program code including computer operating instructions. More specifically, the memory may include a read-only memory (ROM), other types of static storage devices that may store static information and instructions, a Random Access Memory (RAM), other types of dynamic storage devices that may store information and instructions, a magnetic disk storage, a flash, and so forth.
The processor may be a general-purpose processor, such as a general-purpose Central Processing Unit (CPU), microprocessor, etc., an application-specific integrated circuit (ASIC), or one or more ics for controlling the execution of programs in accordance with the inventive arrangements. But may also be a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), an off-the-shelf programmable gate array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components.
The input device may include means for receiving data and information input by a user, such as a keyboard, mouse, camera, scanner, light pen, voice input device, touch screen, pedometer, or gravity sensor, among others.
Output devices may include devices that allow output of information to a user, such as a display screen, printer, speakers, etc.
The communication interface may include any means for using a transceiver or the like to communicate with other devices or communication networks, such as ethernet, a Radio Access Network (RAN), a Wireless Local Area Network (WLAN), etc.
The processor executes the program stored in the memory, and invokes other devices, which can be used to implement the steps of the energy efficiency and carbon emission calculation method of any data center provided by the above embodiments of the present application.
The electronic equipment can also comprise a display component and a voice component, the display component can be a liquid crystal display screen or an electronic ink display screen, and the input device of the electronic equipment can be a touch layer covered on the display component, a key, a track ball or a touch pad arranged on the shell of the electronic equipment, an external keyboard, a touch pad or a mouse and the like.
It will be appreciated by those skilled in the art that the structure shown in fig. 14 is a block diagram of only a portion of the structure associated with the solution of the present description, and does not constitute a limitation on the electronic device to which the solution of the present description applies, and that a particular electronic device may include more or fewer components than those shown in the drawings, or may combine certain components, or have a different arrangement of components.
In addition to the above methods and apparatus, the energy efficiency and carbon emission calculation method of a data center provided by the embodiments of the present specification may be a computer program product including computer program instructions that, when executed by a processor, cause the processor to perform the steps of the energy efficiency and carbon emission calculation method of a data center according to various embodiments of the present specification described in the "exemplary methods" section above of the present specification.
The computer program product may be written with program code for performing the operations of embodiments of the present specification in any combination of one or more programming languages, including an object oriented programming language such as Java, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server.
Furthermore, the present specification embodiment also provides a computer-readable storage medium on which a computer program is stored, the computer program being executed by a processor to perform the steps in the energy efficiency and carbon emission calculation method of a data center according to various embodiments of the present specification described in the above section "exemplary method" of the present specification.
It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above may be implemented by hardware instructions of a computer program, which may be stored in a non-volatile computer-readable storage medium, and when executed, may include the processes of the embodiments of the methods described above. Any reference to memory, storage, databases, or other media used in the embodiments provided herein may include non-volatile and/or volatile memory. Non-volatile memory can include read-only memory (ROM), programmable ROM (PROM), electrically Programmable ROM (EPROM), electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double Data Rate SDRAM (DDRSDRAM), enhanced SDRAM (ESDRAM), synchronous Link DRAM (SLDRAM), rambus (Rambus) direct RAM (RDRAM), direct Rambus Dynamic RAM (DRDRAM), and Rambus Dynamic RAM (RDRAM), among others.
The technical features of the above embodiments can be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the above embodiments are not described, but should be considered as the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several implementation modes of the present specification, and the description thereof is specific and detailed, but not construed as limiting the scope of the solutions provided by the embodiments of the present specification. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present description, which falls within the scope of protection of the present description. Therefore, the protection scope of the patent in the specification shall be subject to the appended claims.

Claims (14)

1. A method for calculating energy efficiency and carbon emission of a data center is characterized by comprising the following steps:
acquiring energy efficiency parameters of the data center, wherein the energy efficiency parameters comprise resource use efficiency, force calculation use rate and force calculation energy efficiency;
determining respective weights corresponding to the energy efficiency parameters of the data center, and determining comprehensive energy efficiency of the data center according to the energy efficiency parameters of the data center and the respective weights corresponding to the energy efficiency parameters, wherein the comprehensive energy efficiency is used for calculating carbon emission of the data center.
2. The method according to claim 1, wherein the determining the comprehensive energy efficiency of the data center according to the energy efficiency parameter of the data center and the weight corresponding to each energy efficiency parameter comprises:
and taking the sum of the energy efficiency parameters of the data center and the products of the weights corresponding to the energy efficiency parameters as the comprehensive energy efficiency of the data center.
3. The method of claim 2, further comprising:
acquiring a first typical value, a second typical value and a third typical value which respectively correspond to the energy efficiency parameters, wherein the first typical value represents a typical value when the corresponding energy efficiency parameter is in a first energy efficiency interval, the second typical value represents a typical value when the corresponding energy efficiency parameter is in a second energy efficiency interval, and the third typical value represents a typical value when the corresponding energy efficiency parameter is in a third energy efficiency interval; when the energy efficiency parameters are in the first energy efficiency interval, the second energy efficiency interval and the third energy efficiency interval, the represented energy efficiency is reduced in sequence;
taking the sum of products of the first typical value corresponding to each energy efficiency parameter and the weight corresponding to each energy efficiency parameter as a first energy efficiency typical value;
taking the sum of products of the second typical value corresponding to each energy efficiency parameter and the weight corresponding to each energy efficiency parameter as a second energy efficiency typical value;
taking the sum of products of the third typical value corresponding to each energy efficiency parameter and the weight corresponding to each energy efficiency parameter as a third energy efficiency typical value;
determining a first critical value between the first energy efficiency typical value and the second energy efficiency typical value;
determining a second critical value between the second energy efficiency typical value and the third energy efficiency typical value;
and determining an energy efficiency state of the data center according to the magnitude relation between the comprehensive energy efficiency of the data center and the first critical value and the second critical value, wherein the energy efficiency state is used for representing the excellent grade of the comprehensive energy efficiency of the data center.
4. The method of claim 3, further comprising:
determining an energy efficiency reference value of the data center according to the first critical value and the second critical value;
and determining a carbon emission reference value of the data center according to the energy efficiency reference value of the data center.
5. The method of claim 3, further comprising:
and updating the first typical value, the second typical value and the third typical value corresponding to the energy efficiency parameters at preset intervals, and returning the sum of the products of the first typical value corresponding to each energy efficiency parameter and the weight corresponding to each energy efficiency parameter as a first energy efficiency typical value.
6. The method of claim 3, further comprising:
and generating an energy efficiency optimization report according to the energy efficiency parameter of the data center and the size relationship of the first typical value, the second typical value and the third typical value corresponding to the energy efficiency parameter.
7. The method according to claim 1, wherein the obtaining energy efficiency parameters of the data center comprises:
acquiring operation parameters of the data center, wherein the operation parameters are used for representing resources used by the data center, a calculation force using state and calculation force generated by the data center;
and calculating the energy efficiency parameter of the data center according to the operation parameter.
8. The method of claim 7, wherein the obtaining operational parameters of the data center comprises:
acquiring the total power consumption of the data center, the power consumption of the IT equipment, the total processor resources of the data center, the used processor resources of the data center, the total power of the IT equipment and the computing power of the data center;
the calculating the energy efficiency parameter of the data center according to the operation parameter comprises:
taking the ratio of the power consumption of the IT equipment to the total power consumption of the data center as the resource utilization efficiency of the data center;
taking the ratio of the difference value of the total processor resources of the data center and the used processor resources to the total processor resources of the data center as a representation value of the computing power utilization rate of the data center;
and taking the ratio of the total power of the IT equipment to the computing power of the data center as the computing power energy efficiency of the data center, and taking the ratio of the difference value between the computing power energy efficiency of the data center and the reference computing power energy efficiency in the reference computing power energy efficiency as the computing power energy efficiency of the data center.
9. The method according to any one of claims 1-8, wherein the determining the respective weights for the energy efficiency parameters of the data center comprises:
and determining weights corresponding to the energy efficiency parameters of the data center according to the attributes of the data center, wherein the attributes of the data center are used for representing the type, the operating environment and the operating state of the data center.
10. A method for calculating energy efficiency and carbon emission of a data center is characterized by comprising the following steps:
the method comprises the steps of obtaining energy efficiency parameters of a data center, wherein the energy efficiency parameters are used for representing resource use efficiency and calculation power use and output states of the data center;
and integrating energy efficiency parameters of the data center and determining the integrated energy efficiency of the data center.
11. An energy efficiency and carbon emission computing device of a data center, comprising:
the first energy efficiency acquisition module is used for acquiring energy efficiency parameters of the data center, wherein the energy efficiency parameters comprise resource utilization efficiency, calculated force utilization rate and calculated force energy efficiency;
the first energy efficiency determining module is used for determining respective corresponding weights of energy efficiency parameters of the data center, and determining comprehensive energy efficiency of the data center according to the energy efficiency parameters of the data center and the respective corresponding weights of the energy efficiency parameters, wherein the comprehensive energy efficiency is used for calculating carbon emission of the data center.
12. An electronic device, comprising: a memory and a processor;
wherein the memory is connected with the processor and is used for storing programs;
the processor is configured to implement the energy efficiency and carbon emission calculation method of the data center according to any one of claims 1 to 10 by executing the program stored in the memory.
13. A storage medium having stored thereon a computer program which, when executed by a processor, implements the energy efficiency and carbon emission calculation method of a data center according to any one of claims 1 to 10.
14. A data center, comprising: the data center comprises IT equipment and accounting equipment connected with the IT equipment, wherein the accounting equipment is used for realizing the energy efficiency and carbon emission calculation method of the data center in any one of claims 1-10.
CN202211027486.9A 2022-08-25 2022-08-25 Energy efficiency and carbon emission calculation method and device for data center and electronic equipment Pending CN115358859A (en)

Priority Applications (2)

Application Number Priority Date Filing Date Title
CN202211027486.9A CN115358859A (en) 2022-08-25 2022-08-25 Energy efficiency and carbon emission calculation method and device for data center and electronic equipment
PCT/CN2023/114509 WO2024041578A1 (en) 2022-08-25 2023-08-23 Energy efficiency and carbon emission calculation method and apparatus for data center, and electronic device

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN202211027486.9A CN115358859A (en) 2022-08-25 2022-08-25 Energy efficiency and carbon emission calculation method and device for data center and electronic equipment

Publications (1)

Publication Number Publication Date
CN115358859A true CN115358859A (en) 2022-11-18

Family

ID=84004737

Family Applications (1)

Application Number Title Priority Date Filing Date
CN202211027486.9A Pending CN115358859A (en) 2022-08-25 2022-08-25 Energy efficiency and carbon emission calculation method and device for data center and electronic equipment

Country Status (2)

Country Link
CN (1) CN115358859A (en)
WO (1) WO2024041578A1 (en)

Cited By (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116128159A (en) * 2023-04-04 2023-05-16 苏州电器科学研究院股份有限公司 Transformer product carbon footprint accounting method and system
CN117236569A (en) * 2023-11-09 2023-12-15 阿里云计算有限公司 IDC carbon emission data processing method, device and medium based on cloud computing
WO2024041578A1 (en) * 2022-08-25 2024-02-29 杭州阿里巴巴飞天信息技术有限公司 Energy efficiency and carbon emission calculation method and apparatus for data center, and electronic device

Family Cites Families (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112561319A (en) * 2020-12-14 2021-03-26 清华大学 Comprehensive evaluation method for energy system of data center
CN114240249A (en) * 2021-12-31 2022-03-25 中国人民武装警察部队工程大学 Comprehensive evaluation system and method for green data center based on entropy weight method
CN115358859A (en) * 2022-08-25 2022-11-18 阿里巴巴（中国）有限公司 Energy efficiency and carbon emission calculation method and device for data center and electronic equipment

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
WO2024041578A1 (en) * 2022-08-25 2024-02-29 杭州阿里巴巴飞天信息技术有限公司 Energy efficiency and carbon emission calculation method and apparatus for data center, and electronic device
CN116128159A (en) * 2023-04-04 2023-05-16 苏州电器科学研究院股份有限公司 Transformer product carbon footprint accounting method and system
CN117236569A (en) * 2023-11-09 2023-12-15 阿里云计算有限公司 IDC carbon emission data processing method, device and medium based on cloud computing
CN117236569B (en) * 2023-11-09 2024-04-19 阿里云计算有限公司 IDC carbon emission data processing method, device and medium based on cloud computing

Also Published As

Publication number Publication date
WO2024041578A1 (en) 2024-02-29

Similar Documents

Publication Publication Date Title
CN115358859A (en) Energy efficiency and carbon emission calculation method and device for data center and electronic equipment
Jafari et al. Decarbonizing power systems: A critical review of the role of energy storage
Wei et al. Economic dispatch savings in the coal-fired power sector: An empirical study of China
Lyu et al. Optimal sizing of energy station in the multienergy system integrated with data center
Wang et al. Role of electrolytic hydrogen in smart city decarbonization in China
CN103455852A (en) Power transmission and distribution cost allocation method based on DEA cooperative game
Sun et al. Colocation demand response: Joint online mechanisms for individual utility and social welfare maximization
Lin et al. Is the implementation of the Increasing Block Electricity Prices policy really effective?---Evidence based on the analysis of synthetic control method
CN110929979A (en) Method and system for measuring and calculating transaction scale of renewable energy excess consumption
Kumar et al. An optimized framework of the integrated renewable energy and power quality model for the smart grid
Liu et al. Evaluation on regional science and technology resources allocation in China based on the zero sum gains data envelopment analysis
CN103606056A (en) Electrical degree power fare immediate computing system and method
CN116843152A (en) Electric power-data service-oriented Internet data center double-layer planning method
CN102902878B (en) A kind of energy cost perception dispatching method
CN116468302A (en) Building park energy structure evaluation method, system, electronic equipment and storage medium
Tang et al. Economic Analysis of Emerging Integrated Energy Service Market in China: A Theoretical View
CN204391747U (en) A kind of interactive Clean-electric system
CN109980697B (en) Renewable energy distribution and consumption method considering quota system
Zheng et al. Lifecycle cost and carbon implications of residential solar-plus-storage in California
Guo et al. A periodic requests dispatcher for energy optimization of hybrid powered data centers
CN116632930B (en) Intelligent control method, system, medium and equipment for renewable energy and commercial power
CN117236569B (en) IDC carbon emission data processing method, device and medium based on cloud computing
Dong et al. Analysis of dynamic renewable energy generation efficiency and its influencing factors considering cooperation and competition between decision-making units: a case study of China
Rui et al. Characterization of the Regulation Capacity of Flexible Loads Represented by Air-conditioning Temperature-controlled Loads
Yu et al. Synergy level measurement and optimization models for the supply-transmission-demand-storage system for renewable energy

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination