CN112561319A - Comprehensive evaluation method for energy system of data center - Google Patents

Comprehensive evaluation method for energy system of data center Download PDF

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CN112561319A
CN112561319A CN202011474635.7A CN202011474635A CN112561319A CN 112561319 A CN112561319 A CN 112561319A CN 202011474635 A CN202011474635 A CN 202011474635A CN 112561319 A CN112561319 A CN 112561319A
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data center
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余占清
屈鲁
韩雪姣
胡茂良
崔康生
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Tsinghua University
Sichuan Energy Internet Research Institute EIRI Tsinghua University
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Sichuan Energy Internet Research Institute EIRI Tsinghua University
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    • 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
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Abstract

According to the comprehensive evaluation method for the energy system of the data center, the common evaluation indexes of the existing data center are comprehensively considered, four evaluation indexes suitable for the energy system of the data center are selected, and the characteristics of the energy system of the data center can be comprehensively reflected; meanwhile, a specific calculation method of each evaluation index is provided, a quantitative calculation result can be obtained, and single-factor evaluation of each index is obtained according to an expert experience method; and finally, determining the index weight value by using a method of an analytic hierarchy process and a fuzzy comprehensive evaluation method, and obtaining a comprehensive evaluation result. And finally, giving comprehensive, scientific and reasonable evaluation to the energy system architecture.

Description

Comprehensive evaluation method for energy system of data center
Technical Field
The invention belongs to the technical field of energy evaluation, and particularly relates to a comprehensive evaluation method for a data center energy system.
Background
The comprehensive evaluation system and the comprehensive evaluation method for researching the data center energy system architecture can provide comprehensive, scientific and reasonable guidance for evaluation and comparison and selection of data center energy system schemes.
The method is characterized in that an evaluation system of a green data center is researched at home and abroad, but a complete and acknowledged evaluation system is not formed because a single evaluation index in a certain aspect is evaluated; or the evaluation system (including resource utilization, operation and maintenance management and the like) aiming at the data center is not suitable for comprehensive evaluation of the energy system architecture concerned by the project; and moreover, the evaluation indexes in the aspect of green environmental protection are emphasized, and comprehensive, scientific and reasonable evaluation on the energy system architecture is difficult to give. Therefore, the project provides a comprehensive evaluation system and method suitable for a data center energy system.
Disclosure of Invention
Aiming at the problems, the invention provides a comprehensive evaluation method of a data center energy system, which comprises the following steps:
step a, determining an evaluation index system;
b, determining a calculation method of each index in the evaluation index system;
c, distributing the weight of each index;
and d, determining a comprehensive evaluation result by using a fuzzy comprehensive evaluation method based on the steps b and c.
Further, in the step a, the evaluation index system comprises a system efficiency dimension, an availability dimension, an economic dimension and an environmental protection dimension; wherein the system efficiency dimension index is power efficiency; the availability dimension index is the system availability; the economic dimension index is a net present value; the environmental protection dimension index is carbon emission reduction ratio.
Further, in the step b, determining a calculation method of each index in the evaluation index system, wherein each index in the evaluation index system comprises power efficiency, system availability, net present value and carbon emission reduction ratio;
the power efficiency calculation method is expressed as:
Figure BDA0002834817130000021
wherein E isoutExpressed as the total output power of the energy supply system; einExpressed as total input power of the energy supply system
Further, the system availability calculation method comprises the following steps:
step b1, calculating the availability of the element:
the availability of the ith element is expressed as: a. thei＝MTBFi/(MTBFi+ MTTR), wherein MTBFiMean time to failure, expressed as ith element: MTBF (methyl tert-butyl ether)i1/λ; MTTR expressed as mean repairable time; λ is expressed as failure rate, i.e. the number of failures occurring per hour;
step b2, calculating the availability of the system:
the availability of a series system is expressed as: a ═ A1A2……Ai(ii) a Wherein, A is expressed as system availability; the availability of a parallel system is expressed as:
Figure BDA0002834817130000022
where A' represents the unavailability of the ith cell.
Further, the method for calculating the net present value NPV comprises:
Figure BDA0002834817130000023
wherein R isiExpressed as the return on investment for the investment project in the i-th year; ciExpressed as the investment cost of the investment project in the i-th year; m represents the discount rate; c0Expressed as the initial cash outflow of the investment plan.
Further, the carbon emission reduction ratio calculation method includes the steps of:
step b3, calculating annual carbon emission reduction:
ΔC＝C0-C1＝μ·(P1t1+P2t2)·k·(1/η0)-μ·[(P1t1+P2t2)·k-P3·t3](1/η1) (ii) a Where C0 represents the average efficiency as eta0Annual carbon emissions in hours; c1 expressed as mean efficiency η1Annual carbon emissions in hours; c0 ═ μ · (P)1t1+P2t2)·k·(1/η0)；C1＝μ·[(P1t1+P2t2)·k-P3·t3](1/η1) (ii) a Mu is expressed as a regional power grid baseline carbon emission factor; p1Representing the generated power of the IT equipment of the data center; p2The generated power expressed as the rated load of the refrigeration equipment; p3Generated power expressed as clean energy; t is t1Expressed as the number of annual hours of use of the data center IT equipment; t is t2Expressed as the number of annual hours of use of the refrigeration equipment; t is t3Expressed as the number of annual hours of clean energy usage; k is expressed as the equipment load rate; eta1Expressed as the actual efficiency of the energy supply system; eta0Expressed as the average efficiency of the energy supply system;
step b4, calculating the carbon emission reduction ratio: Δ G% ═ Δ C/C0.
Further, in the step c, an analytic hierarchy process is adopted to distribute the index weights, and the distribution of the index weights comprises the following steps:
step c1, establishing a hierarchical structure model;
step c2, constructing a judgment matrix according to the hierarchical structure model;
step c3, carrying out consistency check on the judgment matrix:
the consistency ratio CR is expressed as: CR is CI/RI; wherein CI is expressed as a consistency index; CI ═ pmax-n)/(n-1); RI is expressed as the average random consistency index; p is a radical ofmaxRepresenting the maximum characteristic root of the judgment matrix; n is expressed as the order of the judgment matrix;
step c4, calculating the maximum characteristic root p of the judgment matrixmaxCorresponding feature vector V: v ═ V1,v2…vn](ii) a Calculating the direction of the featureTransposed matrix V of quantity VTThe transposed matrix V isTNormalizing to obtain the weight vector W ═ W of each index1,w2…wn]。
Further, the step d of determining the comprehensive evaluation result comprises the following steps:
d1, performing single-factor evaluation on each index in the evaluation index system to determine a single-factor evaluation vector of each index, wherein each index in the evaluation index system comprises power efficiency, system availability, net present value and carbon emission reduction ratio;
d2, respectively taking the single-factor evaluation vectors of each index as row vectors to construct a comprehensive evaluation matrix, wherein the comprehensive evaluation matrix is expressed as:
Figure BDA0002834817130000031
r1a single factor evaluation vector expressed as the power efficiency; r is2A single factor evaluation vector expressed as the system availability; r is3A single factor evaluation vector expressed as the net present value; r is4A single factor evaluation vector expressed as the carbon rejection ratio;
the single-factor evaluation vector of the power efficiency, the single-factor evaluation vector of the system availability, the single-factor evaluation vector of the net present value and the single-factor evaluation vector of the carbon emission reduction ratio are equally divided into five grades of poor, common, good and good;
step d3, obtaining the comprehensive evaluation result according to the comprehensive evaluation matrix, wherein the comprehensive evaluation result matrix is expressed as:
Figure BDA0002834817130000041
b1a weight expressed as that the evaluation grade corresponding to the comprehensive evaluation result is poor; b2Expressing that the corresponding evaluation grade of the comprehensive evaluation result is poor weight; b3The evaluation grade corresponding to the comprehensive evaluation result is expressed as a general weight; b4Expressed as the corresponding evaluation grade of the comprehensive evaluation resultIs a better weight; b5Expressing the weight of the comprehensive evaluation result which is good corresponding to the evaluation grade;
the score of the comprehensive evaluation result is expressed as: b ═ b1*1+b2*2+b3*3+b4*4+b5*5。
The invention also provides a comprehensive evaluation system of the data center energy system, which is characterized by comprising the following components:
the evaluation index system determining unit is used for determining an evaluation index system;
the index calculation method determination unit is used for determining each index calculation method in the evaluation index system;
the weight distribution unit is used for distributing the weights of the indexes;
and the comprehensive evaluation result determining unit is used for determining a comprehensive evaluation result.
Further, the index calculation method determination unit is configured to determine each index calculation method in the evaluation index system, and includes the following steps:
each index in the evaluation index system comprises power efficiency, system availability, net present value and carbon emission reduction ratio;
the power efficiency index calculation method is represented as:
Figure BDA0002834817130000051
wherein E isoutExpressed as the total output power of the energy supply system; einExpressed as the total input power of the energy supply system;
the system availability index calculation method comprises the following steps:
step b1, calculating the availability of the element: the availability of the ith element is expressed as: a. thei＝MTBFiV. (MTBF + MTTR), where MTBFiMean time to failure, expressed as ith element: MTBF (methyl tert-butyl ether)i1/q is 1/(a/8760); a is expressed as annual failure rate; MTTR expressed as mean repairable time; q is expressed as failure rate, i.e., the number of failures occurring per hour;
step b2, the computing system canDegree of use: the availability of a series system is expressed as: a ═ A1A2……Ai(ii) a Wherein A isiExpressed as the availability of the ith element; a is expressed as system availability; the availability of a parallel system is expressed as:
Figure BDA0002834817130000052
wherein, A' represents the unavailability of the ith unit;
the net present value index calculation method is represented as: the net present value index calculation method is represented as:
Figure BDA0002834817130000053
wherein R isiExpressed as the return on investment for the investment project in the i-th year; ciExpressed as the investment cost of the investment project in the i-th year; m represents the discount rate; c0An initial cash outflow expressed as an investment plan;
step b3, calculating carbon emission reduction:
ΔC＝C0-C1＝μ·(P1t1+P2t2)·k·(1/η0)-μ·[(P1t1+P2t2)·k-P3·t3](1/η1)；
where C0 represents the average efficiency as eta0Annual carbon emissions in hours; c1 expressed as mean efficiency η1Annual carbon emissions in hours; c0 ═ μ · (P)1t1+P2t2)·k·(1/η0)；
C1＝μ·[(P1t1+P2t2)·k-P3·t3](1/η1) (ii) a Mu is expressed as a regional power grid baseline carbon emission factor; p1Representing the generated power of the IT equipment of the data center; p2The generated power expressed as the rated load of the refrigeration equipment; p3Generated power expressed as clean energy; t is t1Expressed as the number of annual hours of use of the data center IT equipment; t is t2Expressed as the number of annual hours of use of the refrigeration equipment; t is t3Expressed as the number of annual hours of clean energy usage; k is expressed as a load factor;η1expressed as the actual efficiency of the energy supply system; eta0Expressed as the average efficiency of the energy supply system;
step b4, calculating the carbon emission reduction ratio: Δ G% ═ Δ C/C0.
According to the comprehensive evaluation method for the energy system of the data center, the common evaluation indexes of the existing data center are comprehensively considered, four evaluation indexes suitable for the energy system of the data center are selected, and the characteristics of the energy system of the data center can be comprehensively reflected; meanwhile, a specific calculation method of each evaluation index is provided, a quantitative calculation result can be obtained, and single-factor evaluation of each index is obtained according to an expert experience method; and finally, determining the index weight value by using a method of an analytic hierarchy process and a fuzzy comprehensive evaluation method, and obtaining a comprehensive evaluation result. And finally, giving comprehensive, scientific and reasonable evaluation to the energy system architecture.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
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In order to more clearly illustrate the embodiments of the present invention 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, and it is obvious that the drawings in the following description are some embodiments of the present invention, and those skilled in the art can also obtain other drawings according to the drawings without creative efforts.
FIG. 1 is a schematic diagram of a data center energy system evaluation architecture in an embodiment of the invention;
FIG. 2 is a schematic flow chart illustrating a comprehensive evaluation method for a data center energy system according to an embodiment of the invention;
fig. 3 shows a detailed flow diagram of a comprehensive evaluation method for a data center energy system in an embodiment of the invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention provides a comprehensive evaluation method of a data center energy system architecture, and FIG. 2 shows a flow diagram of the comprehensive evaluation method of the data center energy system in the embodiment of the invention; in fig. 2, the comprehensive evaluation method includes the steps of:
step a, determining an evaluation index system; b, determining a calculation method of each index in an evaluation index system; c, distributing the weight of each index; and d, determining a comprehensive evaluation result based on the steps b and c.
Specifically, the evaluation index system in the step a comprises a system efficiency dimension, an availability dimension, an economic dimension and an environmental protection dimension; the system efficiency dimension index is selected as power efficiency, the availability dimension index is selected as system availability, the economic dimension index is selected as net present value, and the environmental protection dimension index is selected as carbon emission reduction ratio.
As shown in fig. 1, fig. 1 is a schematic diagram illustrating an evaluation system structure of a data center energy system in an embodiment of the present invention, and in fig. 1, a comprehensive evaluation index system is constructed from four dimensions of system efficiency, availability, economy, and environmental friendliness of the data center energy system, where specific evaluation indexes are selected as follows: power efficiency, availability, net present value, carbon emission reduction ratio. As shown in fig. 1, the dashed box is an intermediate quantity having a reference meaning in the calculation process, and is not used as an evaluation index.
Fig. 3 is a schematic flow chart illustrating a comprehensive evaluation method for a data center energy system architecture according to an embodiment of the present invention, and the comprehensive evaluation method for the data center energy system architecture illustrated in fig. 1 is specifically described:
step a, determining an evaluation index system;
b, determining a calculation method of each index in an evaluation index system;
specifically, in the step b, determining a calculation method of each index in an evaluation index system, wherein each index in the evaluation index system comprises power efficiency, system availability, net present value and carbon emission reduction ratio;
specifically, the power efficiency index calculation method is represented as:
Figure BDA0002834817130000071
the power efficiency index mainly selects the efficiency of a data center energy supply system, namely the ratio of the output power and the input power of the energy supply system, and reflects the loss of the energy supply system in the energy transmission and conversion processes; wherein E isoutExpressed as the total output power of the energy supply system; einExpressed as the total input power of the energy supply system;
for the calculation method of the system availability, particularly, the data center availability is an important index which comprehensively reflects whether the data center can provide safe, stable and sustainable services.
(1) Index concept
Reliability (Reliability): the capacity of the data center to complete specified services under specified environmental conditions within specified time is referred to. A plurality of indexes reflecting reliability are provided, such as reliability R, failure rate lambda, mean time between failures MTBF and the like; the calculation relationship among the three is as follows: r (t) ═ e-λt；MTBF＝1/λ。
Serviceability: refers to the ability of the system to perform specified functions and the ease with which maintenance can be performed under specified environmental conditions and for specified times. Maintainability is quantified by the mean time to repair MTTR indicator.
Availability (Availability): is the ratio of the normal time to the total time that the system can be used during the use process. The availability synthesis reflects the reliability and maintainability, the availability is quantified by a ratio index-availability, and the calculation formula is as follows: a is MTBF/(MTBF + MTTR).
The system availability index calculation method comprises the following steps:
step b1, calculating the availability of the element: the availability of the ith element is expressed as: a. thei＝MTBFi/(MTBFi+ MTTR), wherein MTBFiMean time to failure, expressed as ith element: MTBF (methyl tert-butyl ether)i1/λ 1/(a/8760); a is expressed as annual failure rate; MTTR expressed as mean repairable time; λ is expressed as the failure rate, i.e. the number of failures occurring per hour.
Specifically, typical failure parameters of a single element are obtained, wherein the typical failure parameters comprise an annual failure rate a (unit (time/station per year) or (time/km per year)) and an average recoverable time MTTR (unit hour), and the availability of the single element is calculated; note here the transition between failure rate λ (the number of failures occurring per hour) and annual failure rate a.
Step b2, calculating the availability of the system:
specifically, the availability of the system is calculated according to the series-parallel relationship of the system, and for a series system (assuming that one system consists of n subsystems, and a system in which a fault occurs in any one of all units forming the system and can cause a fault in the whole system is called a series system); for a parallel system (if a system is composed of n subsystems, as long as one subsystem can work normally, the system in which the whole system can work normally is called a parallel system);
the availability of a series system is expressed as: a ═ A1A2……Ai(ii) a Wherein A isiExpressed as the availability of the ith element; a is expressed as system availability;
the availability of a parallel system is expressed as:
Figure BDA0002834817130000091
where A' represents the unavailability of the ith cell.
In particular, for the availability of the series system, due to AiLess than 1, AiThe smaller the product of (a), so the more cells in series, the lower the system availability; for the availability of parallel systems, the more parallel units, the higher the system availability.
For the economic index calculation method, concretely, a net present value method is adopted for economic evaluation. The following factors are mainly involved in the net present value rate:
initial investment of data center energy supply system: the initial investment of a data center energy supply system is mainly considered as follows: UPS power systems (or HVDC power systems), backup diesel generators, distribution equipment at various levels (generally, transformers, distribution cabinets, switch cabinets, feeder cabinets, etc. led out from a 10kV outgoing line), energy storage equipment, photovoltaic power generation equipment (if any), auxiliary materials such as cables, and engineering management cost. (regardless of the investment in building construction, air conditioning systems, IT equipment, etc.)
The operating cost of the energy supply system of the data center: the operation cost of the data center energy supply system mainly comprises the following steps: fixed asset depreciation costs, electricity consumption costs, labor and maintenance costs. (without considering other costs such as tax). However, when the net present value method is adopted to calculate the cash outflow every year, the depreciation cost of fixed assets is not considered, and only the power consumption cost, the labor cost and the maintenance cost are considered.
The power consumption cost is mainly the power charge consumed by a power distribution network and a power supply system, the labor cost and the maintenance cost are calculated according to 8% of the original investment, and the annual power consumption cost of the power supply system is expressed as follows:
Figure BDA0002834817130000092
wherein, P1Representing the generated power of the IT equipment of the data center; p2The generated power expressed as the rated load of the refrigeration equipment; t is t1Expressed as the number of annual hours of use of the data center IT equipment; t is t2Expressed as the number of annual hours of use of the refrigeration equipment; k is expressed as the equipment load rate; p3Generated power expressed as clean energy; t is t3Expressed as the number of annual hours of clean energy usage; eta is the efficiency of an energy supply system; e is the average electricity price, and e is 0.8 yuan/kwh in the invention.
Data center IT equipment refers to IT related equipment accessories or whole products, belongs to the product of IT trade, for example: notebook computer, desktop computer, router, switch, mouse, keyboard, tablet, camera, multimedia microphone and stereo set etc.
Annual revenue of data center energy supply system: the annual revenue of the data center energy supply system is noted as 0.
Net present value of data center energy supply system: the Net Present Value (NPV) is the difference between the discount of the future cash flow generated by an investment and the investment cost of the project, and is the total future return value-the total original investment.
The net present value index calculation method is represented as:
Figure BDA0002834817130000101
wherein R isiExpressed as the return on investment for the investment project in the i-th year; ciExpressed as the investment cost of the investment project in the i-th year; m represents the discount rate; c0An initial cash outflow expressed as an investment plan;
Figure BDA0002834817130000102
a present value representing a net cash flow for the investment project.
For the method for calculating the environmental protection index, the environmental protection index is mainly measured by carbon emission reduction ratio, and the method for calculating the carbon emission reduction ratio index comprises the following steps:
step b3, calculating annual carbon emission reduction:
ΔC＝C0-C1＝μ·(P1t1+P2t2)·k·(1/η0)-μ·[(P1t1+P2t2)·k-P3·t3](1/η1) (ii) a Where C0 represents the average efficiency as eta0Annual carbon emissions in hours; c1 expressed as mean efficiency η1Annual carbon emissions in hours; c0 ═ μ · (P)1t1+P2t2)·k·(1/η0)；C1＝μ·[(P1t1+P2t2)·k-P3·t3](1/η1) (ii) a Mu is expressed as a regional power grid baseline carbon emission factor; p1Representing the generated power of the IT equipment of the data center; p2Work of electricity generation expressed as rated load of refrigeration equipmentRate; p3Generated power expressed as clean energy; t is t1Expressed as the number of annual hours of use of the data center IT equipment; t is t2Expressed as the number of annual hours of use of the refrigeration equipment; t is t3Expressed as the number of annual hours of clean energy usage; k is expressed as the equipment load rate; eta1Expressed as the actual efficiency of the energy supply system; eta0Expressed as the average efficiency of the energy supply system;
step b4, calculating the carbon emission reduction ratio: Δ G% ═ Δ C/C0.
Specifically, an emission factor method is adopted to calculate the carbon emission of the energy system of the data center, wherein the carbon emission mainly comes from three aspects: the energy saving method is characterized by saving energy (only considering the energy saving amount of an energy supply system, and not considering the energy saving amount of IT equipment and refrigeration equipment), utilizing clean energy (such as photovoltaic) and utilizing low-carbon emission factor energy (such as natural gas).
C, distributing the weight of each index; in the step c, the weights of all indexes are distributed by adopting an analytic hierarchy process, and the distribution of the weights of all indexes comprises the following steps:
step c1, establishing a hierarchical structure model;
specifically, the evaluation index system established by the invention is the basis of the hierarchical structure model. The resulting hierarchical model is shown in table 1:
Figure BDA0002834817130000111
TABLE 1
Step c2, constructing a judgment matrix according to the hierarchical structure model; the relative importance between the indexes of each level is judged by the evaluator or the inviting expert, and a judgment matrix is constructed according to the '1-9 scale method' introduced in the following table.
The step is scored by evaluators or invitation experts and has certain subjectivity. And when in scoring, assigning 1, 3, 5, 7 and 9 in sequence according to the sequence of the same importance, slight importance, obvious importance, strong importance and extreme importance, adding 2, 4, 6 and 8 as intermediate values, and if the importance relationship is opposite, performing reciprocal processing on the assignment to finally form a judgment matrix D. The matrix is judged to be a square matrix, all elements are larger than 0, the elements on the diagonal are 1, and the elements symmetrical about the diagonal are in reciprocal relation with each other. As shown in table 2:
Figure BDA0002834817130000121
TABLE 2
The embodiment of the present invention is illustrated by an example, and the present invention calculates based on the determination shown in table 3 as an example:
Figure BDA0002834817130000122
TABLE 3
The constructed judgment matrix D (comparison of relative importance of indexes B1-B4) is shown in Table 4:
Figure BDA0002834817130000123
TABLE 4
Step c3, carrying out consistency check on the judgment matrix:
the consistency ratio CR is expressed as: CR is CI/RI; wherein CI is expressed as a consistency index; CI ═ pmax-n)/(n-1); RI is expressed as the average random consistency index; p is a radical ofmaxExpressed as the maximum feature root of the decision matrix; n is represented as the order of the decision matrix D.
Specifically, when the CR value is less than 0.1, the matrix is determined to satisfy the consistency check. The RI values of the decision matrix of order K are shown in Table 5 as:
Figure BDA0002834817130000131
TABLE 5
Step c4, calculating the maximum characteristic root p of the judgment matrixmaxCorresponding feature vector V: v ═ V1,v2…vn]Wherein v isnThe average value of a plurality of rows of the nth row elements of the judgment matrix is shown; computing a transposed matrix V of eigenvectors VTTranspose matrix VTNormalizing to obtain each index weight vector W ═ W1,w2…wn]Wherein w isnThe weight value of the n-th index is expressed.
Specifically, the invention only needs to carry out consistency check on the judgment matrix D. The test results are shown in table 6:
Figure BDA0002834817130000132
TABLE 6
According to Table 6, the eigenvector corresponding to the matrix D is judged to be VA＝[1.50,2.21,1,0.30]T(ii) a Normalizing to obtain a first-level index weight vector WA＝[0.30,0.44,0.20,0.06]。
The weights of all indices to the overall target are shown in table 7:
Figure BDA0002834817130000133
TABLE 7
Step d, determining a comprehensive evaluation result based on the steps b and c, wherein the step d comprises the following steps:
d1, performing single-factor evaluation on each index in the evaluation index system to determine a single-factor evaluation vector of each index, wherein each index in the evaluation index system comprises power efficiency, system availability, net present value and carbon emission reduction ratio;
specifically, the evaluation grades are set as (poor, general, good, and good), and single-factor evaluation is performed on four evaluation indexes of the power efficiency eta, the availability A, the net present value NPV, and the carbon emission reduction ratio delta C% respectively.
For single factor evaluation of power efficiency η: through investigation, for the traditional data center, the empirical value interval of the power efficiency eta is assumed to be (eta)1,η2)。
If eta < eta1Then, the evaluation level "difference" is corresponded to, at this time, the one-factor evaluation vector r1＝[1 0 0 0 0](ii) a If eta1≤η＜(η1+(η2-η1) /3)), corresponding to the rating level "poor", in which case the one-factor rating vector r is used1＝[0 1 0 0 0](ii) a If (eta)1+(η2-η1)/3)≤η＜(η1+2(η2-η1) /3), then corresponding to an evaluation level of "general", in which case the one-factor evaluation vector r1＝[0 0 1 0 0](ii) a If (eta)1+2(η2-η1)/3)≤η＜η2Corresponding to the evaluation level "better", the one-factor evaluation vector r at this time1＝[0 0 0 1 0](ii) a If eta is greater than or equal to eta2Then, corresponding to the evaluation level "good", the one-factor evaluation vector r at this time1＝[0 0 0 0 1]。
For the availability a single factor evaluation: through investigation, for the traditional data center, the empirical value interval of the availability A is assumed to be (A)1,A2)。
If A < A1Then, the evaluation level "difference" is corresponded to, at this time, the one-factor evaluation vector r2＝[1 0 0 0 0](ii) a If A1≤A＜(A1+(A2-A1) /3)), corresponding to the rating level "poor", in which case the one-factor rating vector r is used2＝[0 1 0 0 0](ii) a If (A)1+(A2-A1)/3)≤A＜(A1+2(A2-A1) /3), then corresponding to an evaluation level of "general", in which case the one-factor evaluation vector r2＝[0 0 1 0 0](ii) a If (A)1+2(A2-A1)/3)≤A＜A2Corresponding to the evaluation level "better", the one-factor evaluation vector r at this time2＝[0 0 0 1 0](ii) a If A is more than or equal to A2, the evaluation grade is 'good', and the single-factor evaluation vector r is used2＝[0 0 0 0 1]。
For the net present value NPV single factor evaluation: through investigation, for the conventional data center, the empirical value interval of the net current value NPV is assumed to be (NPV)1,NPV2)。
If NPV < NPV1Then corresponds to the commentPrice level "Difference", in which case the one-factor evaluation vector r3＝[1 0 0 0 0](ii) a If NPV1≤NPV＜(NPV1+(NPV2-NPV1) /3)), corresponding to the rating level "poor", in which case the one-factor rating vector r is used3＝[0 1 0 0 0](ii) a If (NPV)1+(NPV2-NPV1)/3)≤NPV＜(NPV1+2(NPV2-NPV1) /3), then corresponding to an evaluation level of "general", in which case the one-factor evaluation vector r3＝[0 0 1 0 0](ii) a If (NPV)1+2(NPV2-NPV1)/3)≤NPV＜NPV2Corresponding to the evaluation level "better", the one-factor evaluation vector r at this time3＝[0 0 0 1 0](ii) a If NPV is not less than NPV2Then, corresponding to the evaluation level "good", the one-factor evaluation vector r at this time3＝[0 0 0 0 1]。
For the single-factor evaluation of the carbon emission reduction ratio Δ C%: through investigation, for the traditional data center, the empirical value interval of the carbon emission reduction ratio delta C% is assumed to be (delta C%1,ΔC％2)。
If Δ C% < Δ C%1Then, the evaluation level "difference" is corresponded to, at this time, the one-factor evaluation vector r4＝[1 0 0 0 0](ii) a If delta C%1≤ΔC％＜(ΔC％1+(ΔC％2-ΔC％1) /3)), corresponding to the rating level "poor", in which case the one-factor rating vector r is used4＝[0 1 0 0 0](ii) a If (Delta C%1+(ΔC％2-ΔC％1)/3)≤ΔC％＜(ΔC％1+2(ΔC％2-ΔC％1) /3), then corresponding to an evaluation level of "general", in which case the one-factor evaluation vector r4＝[0 0 1 0 0](ii) a If (Delta C%1+2(ΔC％2-ΔC％1)/3)≤ΔC％＜ΔC％2Corresponding to the evaluation level "better", the one-factor evaluation vector r at this time4＝[0 0 0 1 0](ii) a If the delta C% is more than or equal to the delta C%2Then, corresponding to the evaluation level "good", the one-factor evaluation vector r at this time4＝[0 0 0 0 1]。
D2, respectively taking the single-factor evaluation vectors of each index as row vectors to construct a comprehensive evaluation matrix, wherein the comprehensive evaluation matrix is expressed as:
Figure BDA0002834817130000151
rijtaking the expansion elements of the four row vectors r1, r2, r3 and r4 obtained in the step d1 as values of 0 or 1, wherein r is1A single factor evaluation vector expressed as power efficiency; r is2A single factor evaluation vector expressed as system availability; r is3A single factor evaluation vector expressed as net present value; r is4A single factor evaluation vector expressed as carbon rejection ratio;
d3, obtaining a comprehensive evaluation result according to the comprehensive evaluation matrix;
specifically, the comprehensive evaluation result matrix is obtained by cross-multiplying the weight vector w and the comprehensive evaluation matrix R,
Figure BDA0002834817130000161
b1the weight expressed as the difference of the comprehensive evaluation result corresponding to the evaluation grade; b2The weight that the corresponding evaluation grade of the comprehensive evaluation result is poor is expressed; b3The general weight corresponding to the evaluation grade is expressed as the comprehensive evaluation result; b4The comprehensive evaluation result is expressed as a better weight corresponding to the evaluation grade; b5The evaluation result is expressed as a weight that is good for the evaluation level.
Specifically, if the full score is 5 points, let b be b ═ b1*1+b2*2+b2*3+b4*4+b5And b represents the score of the comprehensive evaluation result.
Although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present invention.

Claims (10)

1. A comprehensive evaluation method for a data center energy system is characterized by comprising the following steps:
step a, determining an evaluation index system;
b, determining a calculation method of each index in the evaluation index system;
c, distributing the weight of each index;
and d, determining a comprehensive evaluation result by using a fuzzy comprehensive evaluation method based on the steps b and c.
2. The comprehensive evaluation method for the energy system of the data center according to claim 1, wherein in the step a, the evaluation index system comprises a system efficiency dimension, an availability dimension, an economic dimension and an environmental protection dimension; wherein the content of the first and second substances,
the system efficiency dimension index is power efficiency;
the availability dimension index is the system availability;
the economic dimension index is a net present value;
the environmental protection dimension index is carbon emission reduction ratio.
3. The comprehensive evaluation method of the energy system of the data center according to claim 1, wherein in the step b, calculation methods of indexes in the evaluation index system are determined, and the indexes in the evaluation index system comprise power efficiency, system availability, net present value and carbon emission reduction ratio;
the power efficiency calculation method is expressed as:
Figure FDA0002834817120000011
wherein E isoutExpressed as the total output power of the energy supply system; einExpressed as the total input power to the power supply system.
4. The comprehensive evaluation method of the energy system of the data center according to claim 3, wherein the calculation method of the system availability comprises the following steps:
step b1, calculating the availability of the element:
the availability of the ith element is expressed as: a. thei＝MTBFi/(MTBFi+ MTTR), wherein MTBFiMean time to failure, expressed as ith element: MTBF (methyl tert-butyl ether)i1/λ; MTTR expressed as mean repairable time; λ is expressed as failure rate, i.e. the number of failures occurring per hour;
step b2, calculating the availability of the system:
the availability of a series system is expressed as: a ═ A1A2……Ai(ii) a Wherein, A is expressed as system availability;
the availability of a parallel system is expressed as:
Figure FDA0002834817120000021
where A' represents the unavailability of the ith cell.
5. The comprehensive evaluation method of the energy system of the data center according to claim 3, wherein the net present value NPV is calculated by:
Figure FDA0002834817120000022
wherein R isiExpressed as the return on investment for the investment project in the i-th year; ciExpressed as the investment cost of the investment project in the i-th year; m represents the discount rate; c0Expressed as the initial cash outflow of the investment plan.
6. The comprehensive evaluation method of the energy system of the data center according to claim 3, wherein the carbon emission reduction ratio calculation method comprises the following steps:
step b3, calculating annual carbon emission reduction: Δ C-C0-C1 ═ μ (P)1t1+P2t2)·k·(1/η0)-μ·[(P1t1+P2t2)·k-P3·t3](1/η1) (ii) a Where C0 represents the average efficiency as eta0Annual carbon emissions in hours; c1 indicates flatMean efficiency is η1Annual carbon emissions in hours; c0 ═ μ · (P)1t1+P2t2)·k·(1/η0)；C1＝μ·[(P1t1+P2t2)·k-P3·t3](1/η1) (ii) a Mu is expressed as a regional power grid baseline carbon emission factor; p1Representing the generated power of the IT equipment of the data center; p2The generated power expressed as the rated load of the refrigeration equipment; p3Generated power expressed as clean energy; t is t1Expressed as the number of annual hours of use of the data center IT equipment; t is t2Expressed as the number of annual hours of use of the refrigeration equipment; t is t3Expressed as the number of annual hours of clean energy usage; k is expressed as the equipment load rate; eta1Expressed as the actual efficiency of the energy supply system; eta0Expressed as the average efficiency of the energy supply system;
step b4, calculating the carbon emission reduction ratio: Δ G% ═ Δ C/C0.
7. The comprehensive evaluation method of the energy system of the data center according to claim 1, wherein the distribution of the index weights in step c by using an analytic hierarchy process comprises the following steps:
step c1, establishing a hierarchical structure model;
step c2, constructing a judgment matrix according to the hierarchical structure model;
step c3, carrying out consistency check on the judgment matrix:
the consistency ratio CR is expressed as: CR is CI/RI; wherein CI is expressed as a consistency index; CI ═ pmax-n)/(n-1); RI is expressed as the average random consistency index; p is a radical ofmaxRepresenting the maximum characteristic root of the judgment matrix; n is expressed as the order of the judgment matrix;
step c4, calculating the maximum characteristic root p of the judgment matrixmaxCorresponding feature vector V: v ═ V1,v2…vn](ii) a Computing a transposed matrix V of the eigenvector VTThe transposed matrix V isTNormalizing to obtain the index weights of the indexesWeight vector W ═ W1,w2…wn]。
8. The method for comprehensively evaluating the energy system of the data center according to claim 1, wherein the step d of determining the comprehensive evaluation result comprises the following steps:
d1, performing single-factor evaluation on each index in the evaluation index system to determine a single-factor evaluation vector of each index, wherein each index in the evaluation index system comprises power efficiency, system availability, net present value and carbon emission reduction ratio;
d2, respectively taking the single-factor evaluation vectors of each index as row vectors to construct a comprehensive evaluation matrix, wherein the comprehensive evaluation matrix is expressed as:
Figure FDA0002834817120000031
r1a single factor evaluation vector expressed as the power efficiency; r is2A single factor evaluation vector expressed as the system availability; r is3A single factor evaluation vector expressed as the net present value; r is4A single factor evaluation vector expressed as the carbon rejection ratio;
the single-factor evaluation vector of the power efficiency, the single-factor evaluation vector of the system availability, the single-factor evaluation vector of the net present value and the single-factor evaluation vector of the carbon emission reduction ratio are equally divided into five grades of poor, common, good and good;
step d3, obtaining the comprehensive evaluation result according to the comprehensive evaluation matrix, wherein the comprehensive evaluation result matrix is expressed as:
Figure FDA0002834817120000041
b1a weight expressed as that the evaluation grade corresponding to the comprehensive evaluation result is poor; b2Expressing that the corresponding evaluation grade of the comprehensive evaluation result is poor weight; b3The evaluation grade corresponding to the comprehensive evaluation result is expressed as a general weight; b4Is shown asThe comprehensive evaluation result is a better weight corresponding to the evaluation grade; b5Expressing the weight of the comprehensive evaluation result which is good corresponding to the evaluation grade;
the score of the comprehensive evaluation result is expressed as: b ═ b1*1+b2*2+b3*3+b4*4+b5*5。
9. A comprehensive evaluation system for a data center energy system is characterized by comprising:
the evaluation index system determining unit is used for determining an evaluation index system;
the index calculation method determination unit is used for determining each index calculation method in the evaluation index system;
the weight distribution unit is used for distributing the weights of the indexes;
and the comprehensive evaluation result determining unit is used for determining a comprehensive evaluation result.
10. The comprehensive evaluation system of the energy system of the data center according to claim 9, wherein the index calculation method determination unit is configured to determine each index calculation method in the evaluation index system, and comprises the following steps:
each index in the evaluation index system comprises power efficiency, system availability, net present value and carbon emission reduction ratio;
the power efficiency index calculation method is represented as:
Figure FDA0002834817120000042
wherein E isoutExpressed as the total output power of the energy supply system; einExpressed as the total input power of the energy supply system;
the system availability index calculation method comprises the following steps:
step b1, calculating the availability of the element: the availability of the ith element is expressed as: a. thei＝MTBFiV. (MTBF + MTTR), where MTBFiMean time to failure, expressed as ith element: MTBF (methyl tert-butyl ether)i1/q is 1/(a/8760); a is expressed as annual failure rate; MTTR expressed as mean repairable time; q is expressed as failure rate, i.e., the number of failures occurring per hour;
step b2, calculating the availability of the system: the availability of a series system is expressed as: a ═ A1A2……Ai(ii) a Wherein A isiExpressed as the availability of the ith element; a is expressed as system availability; the availability of a parallel system is expressed as:
Figure FDA0002834817120000051
wherein, A' represents the unavailability of the ith unit;
the net present value index calculation method is represented as: the net present value index calculation method is represented as:
Figure FDA0002834817120000052
wherein R isiExpressed as the return on investment for the investment project in the i-th year; ciExpressed as the investment cost of the investment project in the i-th year; m represents the discount rate; c0An initial cash outflow expressed as an investment plan;
step b3, calculating carbon emission reduction:
ΔC＝C0-C1＝μ·(P1t1+P2t2)·k·(1/η0)-μ·[(P1t1+P2t2)·k-P3·t3](1/η1)；
where C0 represents the average efficiency as eta0Annual carbon emissions in hours; c1 expressed as mean efficiency η1Annual carbon emissions in hours; c0 ═ μ · (P)1t1+P2t2)·k·(1/η0)；C1＝μ·[(P1t1+P2t2)·k-P3·t3](1/η1) (ii) a Mu is expressed as a regional power grid baseline carbon emission factor; p1Representing the generated power of the IT equipment of the data center; p2The generated power expressed as the rated load of the refrigeration equipment; p3Generated power expressed as clean energy; t is t1Is expressed as a numberThe number of hours of annual utilization of data center IT equipment; t is t2Expressed as the number of annual hours of use of the refrigeration equipment; t is t3Expressed as the number of annual hours of clean energy usage; k is expressed as a load factor; eta1Expressed as the actual efficiency of the energy supply system; eta0Expressed as the average efficiency of the energy supply system;
step b4, calculating the carbon emission reduction ratio: Δ G% ═ Δ C/C0.
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Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN116485279A (en) * 2023-06-13 2023-07-25 埃睿迪信息技术（北京）有限公司 Equipment information processing method and device based on water management platform
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

Cited By (3)

* 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
CN116485279A (en) * 2023-06-13 2023-07-25 埃睿迪信息技术（北京）有限公司 Equipment information processing method and device based on water management platform
CN116485279B (en) * 2023-06-13 2023-08-29 埃睿迪信息技术（北京）有限公司 Equipment information processing method and device based on water management platform

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