CN116611744B - Comprehensive weighting method for comprehensive evaluation of SOFC combined heat and power system - Google Patents

Comprehensive weighting method for comprehensive evaluation of SOFC combined heat and power system Download PDF

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CN116611744B
CN116611744B CN202310868937.XA CN202310868937A CN116611744B CN 116611744 B CN116611744 B CN 116611744B CN 202310868937 A CN202310868937 A CN 202310868937A CN 116611744 B CN116611744 B CN 116611744B
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罗云
刘荣军
蒋文春
宋明
张玉财
孟辉波
张秀成
张清贵
周帼彦
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China University of Petroleum East China
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Abstract

The invention provides a comprehensive weighting method for comprehensive evaluation of an SOFC cogeneration system, and belongs to a data processing technology of the cogeneration system. The method specifically comprises the following steps: determining all single performances of the comprehensive performance of the SOFC cogeneration system, classifying, and establishing a hierarchical structure model; classifying all single performances according to four category performances; constructing subjective weight of each single performance on the SOFC cogeneration system; objective weights of the single performance indexes on the SOFC cogeneration system are constructed; obtaining the combination weight of each single performance index under the category performance on the category performance according to the subjective weight and the objective weight; expert credibility is established by data standardization processing and combining with a standard normal distribution function; and constructing a weight factor of the influence of each category of performance of the SOFC cogeneration system on the comprehensive performance. The technical scheme of the invention solves the problem that the comprehensive weighting method of the SOFC cogeneration system cannot be objectively evaluated in the prior art.

Description

Comprehensive weighting method for comprehensive evaluation of SOFC combined heat and power system
Technical Field
The invention relates to the technical field of data processing of a cogeneration system, in particular to a comprehensive weighting method for comprehensive evaluation of an SOFC cogeneration system.
Background
At present, a household cogeneration system takes a traditional diesel generator as a main energy supply original, has low power generation efficiency, large noise and serious pollution, has the phenomenon of energy waste, and does not meet the construction requirements of a low-carbon society. The technology of the SOFC (solid oxide fuel cell) cogeneration system converts chemical energy in fuel into electric energy through electrochemical reaction, and the electrochemical reaction is an exothermic process, so that the released heat can be recovered for avoiding energy waste and simultaneously supplying heat to users, thereby achieving the aim of fully utilizing waste heat, and receiving more and more attention due to the advantages of no noise, energy saving, high efficiency, environmental protection and the like of the SOFC cogeneration system.
However, the SOFC cogeneration system is a highly complex system and is composed of numerous subsystems and devices, and the influence of different subsystems and devices on the SOFC cogeneration system is various, and the degree of the influence is also large and small and different. At present, the SOFC cogeneration system is still in the early development stage, the research on the comprehensive evaluation of the whole SOFC cogeneration system is less, few students make comprehensive consideration on the SOFC cogeneration system, and especially the defects of stronger subjectivity and poor objectivity exist in the weight determination method of different evaluation indexes of the SOFC cogeneration system, so that the establishment of the comprehensive weighting method for the comprehensive evaluation of the SOFC cogeneration system has important significance for evaluating the comprehensive performance of the SOFC cogeneration system and developing and commercially popularizing the SOFC cogeneration system.
Therefore, there is a need for a comprehensive weighting method that can objectively evaluate SOFC cogeneration systems.
Disclosure of Invention
The invention mainly aims to provide a comprehensive weighting method for comprehensively evaluating an SOFC cogeneration system, which aims to solve the problems that the SOFC cogeneration system cannot be comprehensively weighted and the SOFC cogeneration system cannot be objectively evaluated in the prior art.
In order to achieve the aim, the invention provides a comprehensive empowerment party for comprehensively evaluating an SOFC cogeneration systemThe method comprises the following steps: s1, determining all single performances of the comprehensive performance of the SOFC cogeneration system, wherein the single performances comprise: the method comprises the steps of classifying all single performances, establishing a hierarchical structure model, and determining the inclusion relation between an upper layer and a lower layer; s2, classifying all single performances of the SOFC cogeneration system according to four category performances j, wherein the method comprises the following steps: running performance, economical performance, environmental protection performance and reliability performance; s3, constructing subjective weight of each single performance of the SOFC cogeneration system on the influence of the single performance of the SOFC cogeneration system on the category performance of the SOFC cogeneration system by adopting a natural index scale analytic hierarchy process; s4, constructing objective weights of the influence of each single performance index on the type of the SOFC cogeneration system under the type of the SOFC cogeneration system by using a CRITIC method; s5, carrying out combination weighting by adopting a multiplication synthesis method according to the subjective weight and the objective weight to obtain the combination weight of each single performance index under the category performance on the category performance; s6, constructing expert credibility by data standardization processing and combining a standard normal distribution function; s7, constructing weight factors of influences of various types of performances of the SOFC cogeneration system on comprehensive performances by adopting a priority diagram method。
Further, step S3 includes: s3.1, establishing a natural index scale of each single performance according to the importance among the single performances under the category performance, and determining the importance among the single performances under the category performance.
S3.2, constructing a comparison judgment matrix between the single performances under the performances of each category, wherein In order to determine the matrix,is a single performanceAnd (3) withRelative to the importance proportion degree of the index of the upper layer of membership,and (3) withIs any two indexes under the performance of a certain category.
S3.3, solving subjective weight of each single performance under each category performance on SOFC cogeneration system category performance。
S3.4, carrying out consistency test on subjective weights of the single performances under each performance.
Further, step S3.3 includes: s3.3.1, normalizing the elements in the judgment matrix A according to columns.
S3.3.2 for each single performanceSubjective weighting of performance impact on belonging categories。
Further, step S3.4 includes: s3.4.1 calculating the maximum feature root of the judgment matrix，The judgment matrix is represented by a graph,the weight matrix is represented by a matrix of weights,，indicating the impact weight of a single performance on the performance of the category.
S3.4.2, calculating a consistency index based on the maximum feature root, wherein Representing the number of indicators under a certain category of performance.
S3.4.3 calculating relative coherency measures based on coherency measures CI, wherein Is an average random consistency index.
S3.4.4, when CR is less than 0.1, the consistency of the judgment matrix is considered to meet the requirement; otherwise, the judgment matrix is adjusted to meet the CR smaller than 0.1.
Further, step S4 includes: and S4.1, processing the positive type index by adopting a formula (1), and processing the negative type index by adopting a formula (2).
（1）。
（2）。
in the formula ,is a single performance indexFirst, theOriginal measured data;is thatDimensionless processed data.
And S4.2, calculating standard deviation of each single performance index, as shown in a formula (3).
（3）。
in the formula ,is a single performance indexAverage value of the measured data of (a);is a single performance indexThe number of measured data of (a);is a single performance indexStandard deviation of the measured data of (2).
S4.3, as shown in the formula (4), calculating the correlation coefficient of m single performance indexesIs a single performance indexAnd single performance indexWherein is a linear correlation coefficient ofAnd (3) withIs any two indexes under the performance of a certain category.
（4）。
S4.4, calculating the information quantity of each single performance index according to a formula (5):
（5）；
in the formula ,is a single performance indexThe amount of information that is included is the amount of information that,is a single performance indexStandard deviation of the measured data of (2); wherein the method comprises the steps ofThe number of the unidirectional performance under the performance of a certain category;
s4.5, calculating objective weights by using a formula (6):
（6）。
further, step S5 specifically includes: obtaining subjective weightObjective weightThen, adopting a multiplication synthesis method to carry out combination weighting to obtain the combination weight of each single performance index under the category performance on the category performanceAs shown in formula (7):
（7）。
further, the step S6 specifically includes: s6.1, searching m-bit experts, and scoring the importance degree of each performance j on the comprehensive performance influence of the SOFC cogeneration system.
S6.2, calculating the average value of performance scores of the m-bit expert for the j-th category, wherein ,represent the firstExpert pair of bitsScoring of individual category performance.
S6.3, calculating standard deviation of performance scoring of the j-th class by m-bit expert。
S6.4, calculating to obtain a standardized value of m-bit expert scoring。
S6.5, calculating the reliability of the obtained m-bit expert scoring by using formulas (8) and (9) 。
（8）。
（9）。
wherein ,representing expert i's scoring value for category performance j.
Further, the step S7 specifically includes: s7.1, selecting the expert in the step S6, and scoring the importance degree of the performance of the n categories on the comprehensive performance of the SOFC cogeneration system.
And S7.2, multiplying the scoring value of the m-bit expert with the credibility weight of the expert to obtain the final scoring value of the m-bit expert for each class performance, and calculating the performance scoring mean value of each class.
And S7.3, comparing the score average values of the various performances in pairs, and judging the importance.
And S7.4, carrying out normalization analysis on the priority diagram weight calculation table based on the comparison result of the step S7.3, and calculating to obtain the weight value of each category performance.
The invention has the following beneficial effects:
the invention discloses a comprehensive weighting method for comprehensively evaluating an SOFC cogeneration system, which comprises the steps of calculating subjective weights of single performances under various performances by an AHP method, calculating objective weights of the single performances based on a CRITIC method, and obtaining the combined weights of the single performances affecting the category performances by a multiplication synthesis method; the credibility of scoring of each expert is obtained through data standardization processing and combination of standard normal distribution functions, so that subjectivity of the expert on index weight and index scoring is reduced; and the influence weight of each type of performance on the comprehensive performance of the SOFC cogeneration system is calculated by adopting an order diagram method, so that the comprehensive performance evaluation of the SOFC cogeneration system is more objective, and the accuracy of the comprehensive performance evaluation of the SOFC cogeneration system is improved.
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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 that are needed in the description of the embodiments or the prior art will be briefly described, and it is obvious that the drawings in the description below are some embodiments of the present invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art. In the drawings:
fig. 1 shows a flow chart of a comprehensive weighting method for comprehensive evaluation of an SOFC cogeneration system according to the invention.
FIG. 2 is a schematic diagram showing an example of the inclusion relationship between upper and lower layers after a hierarchical model is built using the method of the present invention.
Detailed Description
The following description of the embodiments of the present invention will be made apparent and fully in view of the accompanying drawings, in which some, but not all embodiments of the invention are shown. All other embodiments, which can be made by those skilled in the art based on the embodiments of the invention without making any inventive effort, are intended to be within the scope of the invention.
The comprehensive weighting method for comprehensively evaluating the SOFC cogeneration system shown in fig. 1 comprises the following steps: s1, determining all single performances of the comprehensive performance of the SOFC cogeneration system, wherein the single performances comprise: the method comprises the steps of fuel utilization rate, power generation efficiency, unit fuel heat energy generation amount, unit power cost, volume ratio power, tail gas emission gas concentration (SOx), noise level, equipment failure rate and average failure power failure time, classifying all single performances, establishing a hierarchical structure model, and determining the inclusion relationship between upper and lower layers, for example, as shown in fig. 2.
S2, classifying all single performances of the SOFC cogeneration system according to four category performances j, wherein the method comprises the following steps: running performance, economical performance, environmental protection performance and reliability performance.
S3, constructing subjective weight of each single performance of the SOFC cogeneration system on the influence of the single performance of the SOFC cogeneration system on the category performance of the SOFC cogeneration system by adopting a natural index scale Analytic Hierarchy Process (AHP).
Specifically, step S3 includes: s3.1, establishing a natural index scale of each single performance according to the importance among the single performances under the category performance, and determining the importance among the single performances under the category performance, wherein the natural index scale of each single performance is shown in table 1.
Table 1 each individual performance natural index scale.
。
S3.2, constructing a comparison judgment matrix between the single performances under the performances of each category, wherein In order to determine the matrix,is a single performanceAnd (3) withRelative to the importance proportion degree of the index of the upper layer of membership,and (3) withIs any two indexes under the performance of a certain category.
Expert compares each single performance under each performance in pairs to construct a comparison judgment matrixAs shown in tables 2, 3, 4, 5; wherein the method comprises the steps ofIn order to determine the matrix,is a single performanceAnd (3) withThe degree of importance proportion relative to the index of the upper layer of membership.
Table 2 comparative run performance judgment matrix.
Table 3 economic performance comparison judgment matrix.
Table 4 environmental performance comparison judgment matrix.
Table 5 reliability performance comparison judgment matrix.
S3.3, solving subjective weight of each single performance under each category performance on SOFC cogeneration system category performance。
Specifically, step S3.3 includes: s3.3.1, normalizing the elements in the judgment matrix A according to columns.
And adding each column in the judgment matrix, and dividing the numerical value of each column in the judgment matrix by the added numerical value of each column to obtain a normalized judgment matrix, wherein the normalized judgment matrix is shown in tables 6, 7, 8 and 9.
Table 6 comparison judgment matrix after normalizing the running performance.
Table 7 comparison judgment matrix after economic performance normalization.
Table 8 comparison judgment matrix after normalization of environmental protection performance.
Table 9 comparison judgment matrix after reliability normalization.
S3.3.2 for each single performanceSubjective weighting of performance impact on belonging categories。
And adding the comparison judgment matrix subjected to normalization calculation according to the columns according to the rows, and calculating an average value, namely the subjective weight of each single performance affecting the performance of the category. Subjective weights for individual performance at each class of performance are shown in table 10.
Table 10 subjective weights of individual performance impact on runnability.
Table 11 subjective weight of each individual performance impact on economic performance.
Table 12 subjective weights of the impact of individual performance on environmental performance.
Table 13 subjective weights of individual performance impact on reliability performance.
S3.4, carrying out consistency test on subjective weights of the single performances under each performance.
Specifically, step S3.4 includes: s3.4.1 calculating the maximum feature root of the judgment matrix, wherein The judgment matrix is represented by a graph,the weight matrix is represented by a matrix of weights,，the maximum characteristic root of the influence weight which represents the influence weight of a certain single performance on the performance of the category is calculated as 3.0006.
S3.4.2, calculating a consistency index based on the maximum feature root, wherein Representing the number of indicators under a certain category of performance.
S3.4.3 calculating relative coherency measures based on coherency measures CI。
, wherein As an index of the average random consistency,the values of (2) are looked up from the average random consensus index value table as shown in table 14.
Table 14 average random uniformity index value corresponding to different orders。
S3.4.4 whenIf the number of the judgment matrix is smaller than 0.1, the consistency of the judgment matrix is considered to meet the requirement; otherwise, adjusting the judgment matrix to meetLess than 0.1.
The judgment matrix under the conditions of economical performance, environmental protection performance and reliability is a second-order matrix, and the judgment matrix has complete consistency without consistency test.
S4, constructing objective weights of the influence of each single performance index on the SOFC cogeneration system under the SOFC cogeneration system category performance by using a CRITIC method.
Based on the test data obtained by the test, as shown in table 15, objective weights of the influence of each single performance under each category of performance on the category of the SOFC cogeneration system are obtained by using a CRITIC method.
Table 15 individual performance test data.
/>
Specifically, step S4 includes: and S4.1, processing the positive type index with the higher index value by adopting a formula (1), and processing the negative type index with the lower index value by adopting a formula (2).
（1）。
（2）。
in the formula ,is a single performance indexFirst, theOriginal measured data;is thatDimensionless processed data.
The results of the treatment are shown in tables 16, 17, 18 and 19.
Table 16 the dimensionless treatment results of the performance test data.
Table 17 economic performance test data dimensionless treatment results.
Table 18 environmental performance test data dimensionless treatment results.
/>
Table 19 the reliability test data is dimensionless processed.
And S4.2, calculating standard deviation of each single performance index, as shown in a formula (3).
（3）。
in the formula ,is a single performance indexAverage value of the measured data of (a);is a single performance indexThe number of measured data of (a);is a single performance indexStandard deviation of the measured data of (2).
The calculation results are shown in tables 20, 21, 22, and 23.
Table 20 standard deviation after dimensionless run performance test data.
Table 21 standard deviation after dimensionless of the economic performance test data.
Table 22 standard deviation after dimensionless for environmental performance test data.
/>
Table 23 standard deviation after dimensionless reliable performance test data.
S4.3, as shown in the formula (4), calculateCorrelation coefficient of individual performance indexIs a single performance indexAnd single performance indexWherein is a linear correlation coefficient ofAnd (3) withIs any two indexes under the performance of a certain category.
（4）。
The construction results are shown in tables 24, 25, 26, 27.
Table 24 runs a performance correlation coefficient matrix.
Table 25 economic performance correlation coefficient matrix.
Table 26 environmental performance correlation coefficient matrix.
Table 27 shows the reliability performance related coefficient matrix.
And S4.4, calculating the information quantity of each single performance index according to a formula (5).
（5）。
in the formula ,is a single performance indexThe amount of information that is included is the amount of information that,is a single performance indexStandard deviation of the measured data of (2); wherein the method comprises the steps ofThe number of the unidirectional performance under the performance of a certain category; the larger the information amount, the larger the effect of the single performance in the whole evaluation system, and the larger the weight. The calculation results are shown in tables 28, 29, 30, and 31.
Table 28 runs a performance correlation coefficient matrix.
Table 29 economic performance correlation coefficient matrix.
Table 30 environmental performance correlation coefficient matrix.
Table 31 is a reliable performance correlation coefficient matrix.
S4.5, calculating objective weights by using a formula (6): （6）。
the objective weight calculation results are shown in table 32:
table 32 results table of individual performance objective weight calculations.
And S5, carrying out combination weighting by adopting a multiplication synthesis method according to the subjective weight and the objective weight to obtain the combination weight of each single performance index under the category performance on the category performance.
Specifically, step S5 is specifically: obtaining subjective weightObjective weightThen, adopting a multiplication synthesis method to carry out combination weighting to obtain the combination weight of each single performance index under the category performance on the category performanceAs shown in formula (7):
（7）。
the combination weight calculation results are shown in table 33.
Table 33 results table of individual performance objective weight calculations.
。
S6, constructing expert credibility through data standardization processing and combining a standard normal distribution function.
Specifically, step S6 specifically includes: s6.1, searching m-bit expert, and scoring (percentile) the importance degree of each performance j on the comprehensive performance of the SOFC cogeneration system, as shown in table 34.
Table 34 expert scoring score table.
S6.2, calculating the average value of performance scores of the m-bit expert for the j-th category。
wherein ,represent the firstExpert pair of bitsScoring of individual category performance.
The calculation results are shown in Table 35.
Table 35 class performance score averages.
S6.3, calculating standard deviation of performance scoring of the j-th class by m-bit expert。
The calculation results are shown in table 36.
Table 36 class performance scoring standard deviation.
S6.4, calculating to obtain a standardized value of m-bit expert scoring。
Normalized valueThe closer to 0, the expert scoring for category performanceThe closer to the average of all experts scoring for category performance.
The calculation results are shown in Table 37.
Table 37 expert scores normalized values.
S6.5, calculating the reliability of the obtained m-bit expert scoring by using formulas (8) and (9) 。
（8）。
（9）。
wherein ,representing expert i's scoring value for category performance j.
The calculation results are shown in table 38.
Table 38 scores the confidence tables for each expert.
S7, constructing weight factors of influences of various types of performances of the SOFC cogeneration system on comprehensive performances by adopting a priority diagram method。
Specifically, step S7 specifically includes: s7.1, selecting the expert in the step S6, and scoring the importance degree of the performance of the n categories on the comprehensive performance of the SOFC cogeneration system.
The expert in the step S6 is chosen, and the importance degree (percentage) of each performance on the comprehensive performance of the SOFC cogeneration system is marked asRepresents the firstExpert pair of bitsScoring values for individual category performance are shown in table 39.
Table 39 expert scores a table of values.
。
And S7.2, multiplying the scoring value of the m-bit expert with the credibility weight of the expert to obtain the final scoring value of the m-bit expert for each class performance, and calculating the performance scoring mean value of each class.
Scoring each expert for performance of a certain categoryConfidence weight with the expertMultiplying to obtain final score value of the class performanceAnd calculating the performance score mean value of each category:
wherein ,represent the firstExpert pair of bitsScoring values after the individual category performance corrections are shown in table 40.
Table 40 class performance final score values.
And S7.3, comparing the score average values of the various performances in pairs as shown in a table 41, and judging importance, wherein when the score average value is relatively larger, a number is 1 and is relatively important, a number is 0.5 and is equally important, and a number is 0 and is relatively unimportant, so that a priority diagram weight calculation table is obtained.
The scale of the order diagram and the meaning thereof are shown in table 42, and finally an order diagram is obtained as shown in table 43.
Table 41 class performance final score average.
Table 42 is a priority diagram scale and its meaning.
Table 43 class performance priority chart.
S7.4, based on the comparison result of S7.3, carrying out normalization analysis on the priority diagram weight calculation table, and calculating to obtain weight values of the performances of each category。
Adding each row in the priority chart, adding the added result, dividing the added result of each row by the numerical value, and obtaining the weight value of each category of performance; the results are shown in Table 44.
Table 44 category performance weight calculation results.
Influence weight of category performance on comprehensive performance of SOFC combined heat and power systemAnd the impact weight of each single performance on the performance of the belonging categoryThe results are summarized in Table 45.
Table 45 weight summary table.
According to the invention, a hierarchical structure model is established, weights of each single performance on the performance of the category are obtained by utilizing multiplication synthesis method combination weighting, and influence weights of each category performance on the comprehensive performance of the SOFC cogeneration system are obtained by utilizing a coefficient of variation method and an order diagram method, and meanwhile, expert experience and objective data characteristics are considered, so that the comprehensive performance of the SOFC cogeneration system can be evaluated more fair and objective, and the influence of human factors is reduced.
It should be understood that the above description is not intended to limit the invention to the particular embodiments disclosed, but to limit the invention to the particular embodiments disclosed, and that the invention is not limited to the particular embodiments disclosed, but is intended to cover modifications, adaptations, additions and alternatives falling within the spirit and scope of the invention.

Claims (3)

1. The comprehensive weighting method for comprehensively evaluating the SOFC cogeneration system is characterized by comprising the following steps of:
s1, determining all single performances of the comprehensive performance of the SOFC cogeneration system, wherein the single performances comprise: the method comprises the steps of classifying all single performances, establishing a hierarchical structure model, and determining the inclusion relation between an upper layer and a lower layer;
s2, classifying all single performances of the SOFC cogeneration system according to four category performances j, wherein the method comprises the following steps: running performance, economical performance, environmental protection performance and reliability performance;
s3, constructing subjective weight of each single performance of the SOFC cogeneration system on the influence of the single performance of the SOFC cogeneration system on the category performance of the SOFC cogeneration system by adopting a natural index scale analytic hierarchy process;
the step S3 comprises the following steps:
s3.1, establishing a natural index scale of each single performance according to the importance among the single performances under the category performance, and determining the importance among the single performances under the category performance;
s3.2, constructing a comparison judgment matrix between the single performances under the performances of each category, wherein />For judging matrix +.>Is a single item of performance->And->The degree of importance ratio relative to the index of the upper layer of membership, < ->And (3) withAny two indexes under the performance of a certain category;
s3.3, solving subjective weight of each single performance under each category performance on SOFC cogeneration system category performance；
Step S3.3 includes:
s3.3.1, carrying out normalization calculation on the elements in the judgment matrix A according to columns;
s3.3.2 for each single performanceSubjective weight of the influence on the performance of the belonging category>；
S3.4, carrying out consistency test on subjective weights of each single performance under each performance;
s4, constructing objective weights of the influence of each single performance index on the type of the SOFC cogeneration system under the type of the SOFC cogeneration system by using a CRITIC method;
the step S4 includes:
s4.1, processing positive type indexes by adopting a formula (1), and processing negative type indexes by adopting a formula (2);
（1）；
（2）；
in the formula ,is a single performance index->First->Original measured data; />Is->Dimensionless processed data;
s4.2, calculating standard deviation of each single performance index, as shown in a formula (3):
（3）；
in the formula ,is a single performance index->Average value of the measured data of (a); />Is a single performance index->The number of measured data of (a); />Is a single performance index->Standard deviation of the measured data of (2);
s4.3, as shown in the formula (4), calculating the correlation coefficient of m single performance indexesIs a single performance index->And single performance index->Wherein>And->Any two indexes under the performance of a certain category;
（4）；
s4.4, calculating the information quantity of each single performance index according to a formula (5):
（5）；
in the formula ,is a single performance index->Information amount contained->Is a single performance index->Standard deviation of the measured data of (2); wherein->The number of the unidirectional performance under the performance of a certain category;
s4.5, calculating objective weights by using a formula (6):
（6）；
s5, carrying out combination weighting by adopting a multiplication synthesis method according to the subjective weight and the objective weight to obtain the combination weight of each single performance index under the category performance on the category performance;
s6, constructing expert credibility by data standardization processing and combining a standard normal distribution function;
the step S6 specifically comprises the following steps:
s6.1, searching m-bit experts, and scoring the importance degree of each performance j on the comprehensive performance influence of the SOFC cogeneration system;
s6.2, calculating the average value of performance scores of the m-bit expert for the j-th category, wherein ,/>Represent the firstExpert pair->Scoring values for individual category performance;
s6.3, calculating standard deviation of performance scoring of the j-th class by m-bit expert；
S6.4, calculating to obtain a standardized value of m-bit expert scoring；
S6.5, calculating the reliability of the obtained m-bit expert scoring by using formulas (8) and (9) ；
（8）；
（9）；
wherein ,scoring values representing expert i for class performance j;
s7, constructing weight factors of influences of various types of performances of the SOFC cogeneration system on comprehensive performances by adopting a priority diagram method；
The step S7 specifically comprises the following steps:
s7.1, selecting the expert in the step S6, and scoring the importance degree of the n categories of performance on the comprehensive performance influence of the SOFC cogeneration system;
s7.2, multiplying the scoring value of the m-bit expert with the credibility weight of the expert to obtain the final scoring value of the m-bit expert for each class of performance, and calculating the average value of each class of performance scoring;
s7.3, comparing the score average values of the performances of the two classes in pairs, and judging the importance;
and S7.4, carrying out normalization analysis on the priority diagram weight calculation table based on the comparison result of the step S7.3, and calculating to obtain the weight value of each category performance.
2. The comprehensive weighting method for comprehensive evaluation of SOFC cogeneration system of claim 1, wherein step S3.4 comprises:
s3.4.1 calculating the maximum feature root of the judgment matrix, wherein ,/>Representing a judgment matrix->Representing a weight matrix, +.>，/>An influence weight representing the performance of a certain single item on the performance of the category;
s3.4.2, calculating a consistency index based on the maximum feature root, wherein />Representing the number of indexes under the performance of a certain category;
s3.4.3 calculating relative coherency measures based on coherency measures CI, wherein />Is an average random consistency index;
s3.4.4, when CR is less than 0.1, the consistency of the judgment matrix is considered to meet the requirement; otherwise, the judgment matrix is adjusted to meet the CR smaller than 0.1.
3. The comprehensive weighting method for comprehensive evaluation of the SOFC cogeneration system according to claim 1, wherein step S5 specifically comprises: obtaining subjective weightAnd objective weight +.>Then, adopting a multiplication synthesis method to carry out combination weighting to obtain the combination weight of each single performance index under the category performance on the category performance>As shown in formula (7):
（7）。
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