CN112330179B - Fuzzy comprehensive evaluation method for coal blending combustion based on improved entropy weight method - Google Patents

Fuzzy comprehensive evaluation method for coal blending combustion based on improved entropy weight method Download PDF

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CN112330179B
CN112330179B CN202011285884.1A CN202011285884A CN112330179B CN 112330179 B CN112330179 B CN 112330179B CN 202011285884 A CN202011285884 A CN 202011285884A CN 112330179 B CN112330179 B CN 112330179B
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陈思勤
胡涛
李晓辰
沈玉华
刘伟
曹阳
寿星旻
茅大钧
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Shanghai University of Electric Power
Shanghai Shidongkou Second Power Plant of Huaneng Power International Inc
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Abstract

The invention relates to a fuzzy comprehensive evaluation method for coal blending combustion based on an improved entropy weight method, which comprises the following steps: 1) determining an evaluation index set according to factors influencing the selection of the coal blending and burning type; 2) determining a comment set according to the actual condition requirement of blending coal in a power plant; 3) ranking the importance of each evaluation index and determining the weight of each evaluation index in the evaluation index set by adopting an improved entropy weight method; 4) constructing a membership function of each evaluation index on the comment set; 5) obtaining evaluation index parameters corresponding to each coal blending and burning coal quality scheme to be evaluated, and combining the evaluation index parameters according to membership function values of the evaluation indexes to obtain a fuzzy comprehensive judgment matrix; 6) and obtaining a fuzzy comprehensive evaluation result of coal blending and burning through fuzzy transformation according to the fuzzy comprehensive judgment matrix, and determining an optimal coal blending and burning coal quality scheme according to the principle of selecting the maximum membership degree. Compared with the prior art, the method has the advantages of quantitative optimization of the coal blending scheme, high reliability and the like.

Description

Fuzzy comprehensive evaluation method for coal blending combustion based on improved entropy weight method
Technical Field
The invention relates to the field of coal blending combustion in power plants, in particular to a fuzzy comprehensive evaluation method for coal blending combustion based on an improved entropy weight method.
Background
Coal is a main energy source in China, and with the continuous development of economy, the total coal consumption accounts for more than 50% of the total energy consumption, so that the power generation form in China still takes the coal-fired thermal power generating unit as the main energy source for a long time. Because of the shortage of domestic coal resources and the increasing shortage of coal supply, the coal price rises and the coal transportation cost increases, in order to save the comprehensive cost, most power plants try to blend two or more single coals with different coal qualities according to a certain proportion through mechanical processing, so that the comprehensive performance of the blended coal meets the requirement. However, the determination of the blending ratio of the mixed coal is a multi-factor comprehensive evaluation process, the considered factors are many, and if the blending ratio of the mixed coal is not proper, great adverse effects are caused to combustion equipment, such as: insufficient boiler output, unstable combustion, difficult ignition, reduced boiler efficiency, increased cost, serious pollutant discharge and the like.
At present, most power plants adopt a plurality of coal blending optimization algorithms, and each algorithm has various differences in coal blending application, for example, the BP neural network algorithm is most applied, but is influenced by a combustion characteristic database of coal types; the genetic algorithm has good global search performance, but is influenced by great coal variety difference, so that the constraint condition is complex, and the calculation result is not accurate enough; fuzzy comprehensive evaluation can effectively establish fuzzy relations among different coal types, but evaluation index weights need to be set manually, so that the subjectivity is high, and the result credibility is reduced; the evaluation index weight determined by simply applying the entropy weight method is too strong in objectivity, so that the practical significance is lacked, and the research on coal blending combustion has great research significance and value.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provide a fuzzy comprehensive evaluation method for coal blending combustion based on an improved entropy weight method.
The purpose of the invention can be realized by the following technical scheme:
a fuzzy comprehensive evaluation method for coal blending and burning based on an improved entropy weight method is used for obtaining an optimal coal blending and burning coal quality scheme and comprises the following steps:
1) determining an evaluation index set according to factors influencing the selection of the coal blending and burning type;
2) determining a comment set according to the actual condition requirement of blending coal in a power plant;
3) ranking the importance of each evaluation index and determining the weight omega of each evaluation index in the evaluation index set by adopting an improved entropy weight methodi；
4) Constructing a membership function of each evaluation index on the comment set;
5) obtaining evaluation index parameters corresponding to each coal blending and burning coal quality scheme to be evaluated, and combining the evaluation index parameters according to membership function values of the evaluation indexes to obtain a fuzzy comprehensive judgment matrix R;
6) and obtaining a fuzzy comprehensive evaluation result of coal blending and burning through fuzzy transformation according to the fuzzy comprehensive judgment matrix, and determining an optimal coal blending and burning coal quality scheme according to the principle of selecting the maximum membership degree.
In the step 1), each evaluation index in the evaluation index set specifically comprises spontaneous combustion characteristic, grindability characteristic, ignition characteristic, burnout characteristic, flammability characteristic, combustion efficiency, slagging degree, economy, stable combustion characteristic and pollutant emission.
In the step 2), the decisions in the comment set specifically include excellent, good, medium and poor.
The step 3) specifically comprises the following steps:
31) obtaining the importance ranking of each expert on the evaluation index by adopting a Delphi method, and overlapping to form an evaluation index importance ranking matrix A ═ a (a)ij)n×nWherein a isijRanking the number of times of the jth name for the ith index influence degree;
32) determining the weight omega of each evaluation index in the evaluation index set by adopting an improved entropy weight methodi。
In the step 32), the membership function H (T) corresponding to the ranking T obtained after the expert evaluates the ith evaluation index is used as the information entropy, and the evaluation index b (T) of the total m experts to the ith evaluation index is calculated according to the probability f (T) when the ranking of the ith evaluation index is TiAnd obtaining the weight omega of each evaluation index after normalizationi。
The weight ω of each evaluation indexiThe expression of (a) is:
Figure GDA0003200012510000021
Figure GDA0003200012510000022
Figure GDA0003200012510000031
f(aij)＝bij
wherein, bijIs the ith row and the jth column parameter of the rank membership matrix, n is the total number of evaluation indexes, beta is a constant, and beta is n + 2.
In the step 4), among the evaluation indexes, the smaller the stable combustion characteristic and pollutant emission evaluation index parameters are, the better the corresponding comment is, the smaller the evaluation index is, the better the membership function is, and the following are established:
Figure GDA0003200012510000032
Figure GDA0003200012510000033
Figure GDA0003200012510000034
Figure GDA0003200012510000035
among the evaluation indexes, the larger the evaluation index parameters of the ignition characteristic, the burnout characteristic, the combustible characteristic, the economy, the combustion efficiency, the slagging degree, the grindability characteristic and the spontaneous combustion characteristic are, the better the corresponding comment is, the larger the evaluation index is, the better the membership function is, and the following are found:
Figure GDA0003200012510000036
Figure GDA0003200012510000041
Figure GDA0003200012510000042
Figure GDA0003200012510000043
wherein r is1(x)、r2(x)、r3(x)、r4(x) Respectively representing excellent, good, medium and poor membership functions, wherein x is a specific parameter value of each evaluation index in the coal blending and coal burning scheme to be evaluated, and the parameters a, b, c and d are evaluation index standard values in an evaluation index standard table.
The evaluation index standard table specifically comprises:
evaluation index partitioning Is excellent in Good effect Medium and high grade Is poor
Self-ignition characteristics ≥2.8 2.1 1.4 ≤1.0
Abradability feature ≥1.5 1.4 1.3 ≤1.2
Ignition characteristics ≥80 60 40 ≤20
Characteristics of burnout ≥2.0 1.5 1.0 ≤0.5
Combustible characteristic ≥2.4 1.9 1.4 ≤0.9
Efficiency of combustion ≥82.5％ 80％ 77.5％ ≤75％
Degree of slag formation ≥1400 1350 1300 ≤1250
Economy of use ≥1.3 1.1 0.9 ≤0.7
Stable combustion characteristic ≤560 585 610 ≥635
Pollutant discharge ≤0.2 0.4 0.6 ≥0.8
In the step 5), the specific steps for obtaining the evaluation index parameters corresponding to each coal blending and burning coal quality scheme to be evaluated are as follows:
spontaneous combustion behavior KdThe explosive index of the coal dust is used as an evaluation index, and the evaluation index comprises the following components:
Figure GDA0003200012510000051
wherein, VdIs a dry base volatile component of coal, VvqLower limit of combustible volatile matter required for combustion;
the grindability characteristic Kkm includes the following components when the grindability coefficient is used as an evaluation index:
Figure GDA0003200012510000052
wherein E isbzTo grind the power consumption of standard coal, EsPower consumption for milling test coal;
the ignition characteristic index Z is calculated by:
Figure GDA0003200012510000053
wherein, VadFor volatile content, MadIs the moisture content, CadIs the fixed carbon content;
the calculation formula of the burnout characteristic index F is as follows:
F＝(Vad+Mad)2×Cad×100
wherein, VadFor volatile content, MadIs the moisture content, CadIs the fixed carbon content;
the calculation formula of the flammability characteristic index C is:
Figure GDA0003200012510000054
wherein, VadFor volatile content, MadIs the moisture content, AadIs ash content;
the calculation formula of the stable combustion characteristic index T is as follows:
T＝654-1.9Vad+0.43Aad-4.5Mad
wherein, VadFor volatile content, MadIs the moisture content, AadIs ash content;
the economic efficiency E takes the economic index as an evaluation index, and comprises the following components:
Figure GDA0003200012510000055
wherein: qarLow calorific value, VadThe volatile content, S, J, and G are the sulfur content, coal unit price, and coal freight, respectively;
the pollutant emission I takes an environmental protection score index as an evaluation index, and comprises the following steps:
Figure GDA0003200012510000056
Figure GDA0003200012510000057
wherein: vs1Is SO2Lower limit of emission concentration, Vs2Is SO2Upper limit of discharge concentration, VsIs SO2Discharge concentration, λ1Is SO2Index of failure, Vn1Is NOxLower limit of emission concentration, Vn2Is NOxUpper limit of discharge concentration, VnIs NOxDischarge concentration, λ2Is NOxIndex of failure, Vy1Is the smoke emission concentration, Vy2Lower limit of smoke emission concentration, VyAt the upper limit of the soot emission concentration, λ3Is a smoke fault index, n1Is SO2Number of boiler failures due to increased emissions, n2Is NOxNumber of boiler failures due to increased emissions, n3For the number of boiler faults, n, caused by increased smoke emissionsGThe total number of boiler failures;
the combustion efficiency retrieves data from a system database;
the slagging degree takes the softening temperature of the coal ash as an evaluation index, and the data is collected and selected from the reality.
In the step 6), a coal blending fuzzy comprehensive evaluation result is obtained through fuzzy transformation according to the fuzzy comprehensive judgment matrix, and the optimal coal blending coal quality scheme with the largest fuzzy comprehensive evaluation value is selected, and the method specifically comprises the following steps:
B＝ωi T·R＝(B1，B2，…Bi*…，BN*)
wherein B is a comprehensive judgment matrix, N*Total number of coal quality schemes for coal blending combustion to be evaluated, Bi*Is the ith*And (3) carrying out fuzzy comprehensive evaluation on the coal quality blended coal scheme to be evaluated.
Compared with the prior art, the invention has the following advantages:
firstly, the invention combines the problems in the field of coal blending and burning with the fuzzy comprehensive evaluation model, solves the problem of multi-constraint multi-index factors of the coal blending problem of the power plant, not only effectively establishes the fuzzy relation among various factor indexes influencing the coal blending ratio, but also can well quantitatively determine the optimized coal blending model.
The invention adopts the improved entropy weight method and the fuzzy comprehensive evaluation method, thereby not only solving the problem that the objectivity of the entropy weight method is too strong to cause deviation from the actual significance, but also solving the problem that the reliability and the credibility are reduced because the subjectivity of the evaluation index is too strong in the fuzzy comprehensive evaluation.
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FIG. 1 is a flow chart of the method of the present invention.
Detailed Description
The invention is described in detail below with reference to the figures and specific embodiments. Note that the following description of the embodiments is merely a substantial example, and the present invention is not intended to be limited to the application or the use thereof, and is not limited to the following embodiments.
Examples
As shown in FIG. 1, the invention provides a fuzzy comprehensive evaluation method for coal blending combustion based on an improved entropy weight method, which comprises the following steps:
1. the method is characterized by comprehensively considering factors influencing the selection of coal blending and burning coal types in multiple aspects, determining evaluation indexes related to coal blending and burning, reflecting the quality degree of the coal blending and burning ratio from different aspects, wherein each evaluation index is respectively a spontaneous combustion characteristic, a grindable characteristic, an ignition characteristic, a burnout characteristic, a combustible characteristic, combustion efficiency, slagging degree, economy, a stable combustion characteristic and pollutant emission, and the 10 evaluation indexes form an evaluation index system set and are recorded as:
U＝{u1,u2,u3,…,u10} (1)
2. according to the actual condition requirement of blending coal in the power plant, index comments are divided into excellent, good, medium and poor, and 4 different decisions form a comment set which is marked as:
V＝{v1,v2,v3,v4} (2)
actually, the evaluation index set of each evaluation index is divided, and the obtained evaluation index standard is shown in table 1.
TABLE 1 Standard Table of each evaluation index
Evaluation index partitioning Is excellent in Good effect Medium and high grade Is poor
Self-ignition characteristics ≥2.8 2.1 1.4 ≤1.0
Abradability feature ≥1.5 1.4 1.3 ≤1.2
Ignition characteristics ≥80 60 40 ≤20
Characteristics of burnout ≥2.0 1.5 1.0 ≤0.5
Combustible characteristic ≥2.4 1.9 1.4 ≤0.9
Efficiency of combustion ≥82.5％ 80％ 77.5％ ≤75％
Degree of slag formation ≥1400 1350 1300 ≤1250
Economy of use ≥1.3 1.1 0.9 ≤0.7
Stable combustion characteristic ≤560 585 610 ≥635
Pollutant discharge ≤0.2 0.4 0.6 ≥0.8
3. Ranking of importance of evaluation indexes: the method adopts a Delphi method to form the importance of each expert to the evaluation index for sequencing, and comprises the following specific steps:
around the target of' the evaluation index has the largest influence on the coal blending ratio ", m experts are arranged to perform importance ranking on n (10 in the example), each expert corresponds to an evaluation index ranking set matrix, and the ranking set matrices of the m experts are summed to obtain an evaluation index importance ranking matrix, as shown in formula (3):
A＝(aij)n×n,i＝1,2,…,n；j＝1,2,…,n) (3)
in the formula, aijThe number of times of the jth name is ranked for the ith index influence degree is detailed in table 2:
table 2 expert group ranking table for evaluation index
Figure GDA0003200012510000071
Figure GDA0003200012510000081
Assuming that p (X) represents the probability of occurrence of the event X, defining the information entropy of the event X and making the value always located between [0 and 1], as shown in formula (4):
Figure GDA0003200012510000082
let T be the i index u of the expertiAnd (3) modifying the formula (4) into a membership function of T according to the following formula after the ranking number is obtained after evaluation:
H(T)＝-αpi(T)lnpi(T) (5)
in the formula, if the index uiThe degree of influence ranks 1 st, then T-1, and if the degree of influence ranks 2 nd, then T-2, which, similarly, may determine that the range of values for the rank is T-1, 2,3,.., n,
Figure GDA0003200012510000083
let f (T) be the i-th index uiAnd (3) converting the formula (5) to obtain a formula (6) by taking the value of beta as n +2 according to the probability when the rank is t:
Figure GDA0003200012510000084
b is formed byijForming a rank membership matrix, and evaluating the index u by m expertsiThe evaluation index of (A) is represented by the formula (7):
bi＝(bi1+bi2+…+bim)/m (7)
carrying out normalization processing on the evaluation index i to obtain an evaluation index weight shown as a formula (8):
Figure GDA0003200012510000085
ranking the evaluation indexes according to an improved entropy weight method and a professional team in the table 2, wherein the obtained evaluation index weight vector is as follows:
W＝(0.0641,0.0798,0.1308,0.1164,0.1161,0.0983,0.0875,0.0916,0.0894,0.1260)
4. analyzing the characteristics of each evaluation index, selecting and constructing a membership function suitable for each evaluation index, which specifically comprises the following steps:
(1) according to the actual situation, in each evaluation index, the smaller the stable combustion characteristic and pollutant emission evaluation index parameters are, the better the corresponding assessment is, so that the smaller the evaluation index is, the better the membership function is, and the corresponding evaluation index standard in table 1 is, the following are provided:
Figure GDA0003200012510000091
Figure GDA0003200012510000092
Figure GDA0003200012510000093
Figure GDA0003200012510000094
in the formula, r1(x)、r2(x)、r3(x)、r4(x) X is a specific parameter value (obtained from the following step 5) of each evaluation index in the coal blending scheme to be evaluated, and the parameters a, b, c and d respectively correspond to the evaluation index standard values in table 1, for example, in the stable combustion characteristic, a is 560, b is 585, c is 610, d is 635, and so on.
(2) According to the actual situation, the larger the ignition characteristic, the burnout characteristic, the combustible characteristic, the economical efficiency, the combustion efficiency, the slagging degree, the grindability and the spontaneous combustion characteristic evaluation index parameters are, the better the corresponding assessment is, so that a membership function with the larger evaluation index and the better evaluation index is constructed, and the evaluation index standards in the table 1 are as follows:
Figure GDA0003200012510000101
Figure GDA0003200012510000102
Figure GDA0003200012510000103
Figure GDA0003200012510000104
in the formula, r1(x)、r2(x)、r3(x)、r4(x) X is a specific parameter value (obtained from the following step 5) of each evaluation index in the coal blending scheme to be evaluated, and parameters a, b, c and d respectively correspond to the evaluation index standard values in table 1, for example, in the spontaneous combustion characteristic, a is 2.8, b is 2.1, c is 1.4, d is 1.0, and so on.
5. Determining a fuzzy comprehensive judgment matrix R, which comprises the steps of predicting the coal quality of the mixed coal, collecting real-time data of the mixed coal, calculating evaluation index parameters and calculating the fuzzy comprehensive judgment matrix R, and specifically comprises the following steps:
5.1 predicting the coal quality of the mixed coal by using a BP neural network algorithm or a support vector machine algorithm to predict the calorific value, the sulfur content, the volatile content, the moisture, the fixed carbon and the ash content of the mixed coal to obtain necessary parameters for calculating evaluation indexes;
5.2 collecting real-time data of mixed coal includes data of boiler combustion efficiency, softening temperature (slagging degree), spontaneous combustion temperature of coal powder, hardness, strength, toughness, boiler failure rate, coal unit price, coal transportation cost and SO discharge2、NOxAnd smoke and dust;
5.3 the calculation formula for calculating each evaluation index parameter is as follows:
spontaneous combustion behavior KdThe explosiveness index of the coal dust is used as an evaluation index,as shown in equation (17):
Figure GDA0003200012510000111
in the formula, VdIs a dry base volatile component of coal, VvqLower limit of combustible volatile matter required for combustion;
the grindability characteristic Kkm is an evaluation index based on the grindability coefficient, as shown in equation (18):
Figure GDA0003200012510000112
in the formula, EbzTo grind the power consumption of standard coal, EsPower consumption for milling test coal;
the formula for calculating the ignition quality index Z is shown in formula (19):
Figure GDA0003200012510000113
in the formula, VadFor volatile content, MadIs the moisture content, CadIs the fixed carbon content;
the calculation formula of the ember characteristic index F is shown in formula (20):
F＝(Vad+Mad)2×Cad×100 (20)
in the formula, VadFor volatile content, MadIs the moisture content, CadIs the fixed carbon content;
the calculation formula of the flammability characteristic index C is shown in formula (21):
Figure GDA0003200012510000114
in the formula, VadFor volatile content, MadIs the moisture content, AadIs ash content;
the formula for calculating the stable combustion characteristic index T is shown in equation (22):
T＝654-1.9Vad+0.43Aad-4.5Mad (22)
in the formula, VadFor volatile content, MadIs the moisture content, AadIs ash content;
the economic efficiency E is an economic index as an evaluation index, and its calculation formula is shown in formula (23):
Figure GDA0003200012510000115
in the formula: qarLow calorific value, VadThe volatile content, S, J, and G are the sulfur content, coal unit price, and coal freight, respectively;
the pollutant emission I takes an environmental protection score index as an evaluation index, and the calculation formula is shown as formulas (24) and (25):
Figure GDA0003200012510000116
Figure GDA0003200012510000117
in the formula: vs1Is SO2Lower limit of emission concentration, Vs2Is SO2Upper limit of discharge concentration, VsIs SO2Discharge concentration, λ1Is SO2Index of failure, Vn1Is NOxLower limit of emission concentration, Vn2Is NOxUpper limit of discharge concentration, VnIs NOxDischarge concentration, λ2Is NOxIndex of failure, Vy1Is the smoke emission concentration, Vy2Lower limit of smoke emission concentration, VyAt the upper limit of the soot emission concentration, λ3Is a smoke fault index, n1Is SO2Number of boiler failures due to increased emissions, n2Is NOxNumber of boiler failures due to increased emissionsNumber, n3For the number of boiler faults, n, caused by increased smoke emissionsGThe total number of boiler failures;
the combustion efficiency is obtained by calling data from a system database;
the slagging degree is generally determined by taking the softening temperature of coal ash as an evaluation index, and data are collected and selected from the actual.
And 5.4, substituting the mixed coal quality prediction information and the actual condition acquisition data into each evaluation index parameter calculation formula to obtain parameter values of each evaluation index, calculating the membership degree belonging to each comment according to the evaluation index parameters and the comment set standard, and finally combining to form a fuzzy comprehensive judgment matrix R, wherein each column vector in the fuzzy comprehensive judgment matrix R corresponds to 10 evaluation index parameter values contained in each coal blending and burning coal quality scheme to be evaluated.
6. Calculating fuzzy comprehensive evaluation results of coal blending and co-combustion through fuzzy transformation, and determining an optimal coal blending and co-combustion coal quality scheme according to the principle of selecting the maximum membership degree, wherein the fuzzy comprehensive evaluation results specifically comprise the following steps:
obtaining a comprehensive evaluation result through fuzzy transformation F (U) → F (V), wherein the comprehensive evaluation result is shown in a formula (26):
B＝ωi T·R＝(B1，B2，…，BN) (26)
in the formula, B is a comprehensive evaluation matrix, and N is the total number of coal quality schemes to be evaluated.
The maximum membership degree B in the comprehensive evaluation matrixiAnd finally determining the optimal scheme of the ideal coal blending quality ratio by comparing the membership grade sets of different schemes and the membership degree of the membership grade set.
The above embodiments are merely examples and do not limit the scope of the present invention. These embodiments may be implemented in other various manners, and various omissions, substitutions, and changes may be made without departing from the technical spirit of the present invention.

Claims (9)

1. A fuzzy comprehensive evaluation method for coal blending and burning based on an improved entropy weight method is used for obtaining an optimal coal blending and burning coal quality scheme, and is characterized by comprising the following steps:
1) determining an evaluation index set according to factors influencing the selection of the coal blending and burning type;
2) determining a comment set according to the actual condition requirement of blending coal in a power plant;
3) ranking the importance of each evaluation index and determining the weight omega of each evaluation index in the evaluation index set by adopting an improved entropy weight methodi；
4) Constructing a membership function of each evaluation index on the comment set;
5) obtaining evaluation index parameters corresponding to each coal blending and coal blending scheme to be evaluated, combining the evaluation index parameters according to membership function values of the evaluation indexes to obtain a fuzzy comprehensive judgment matrix R, wherein the evaluation index parameters corresponding to each coal blending and coal blending scheme to be evaluated are specifically as follows:
spontaneous combustion behavior KdThe explosive index of the coal dust is used as an evaluation index, and the evaluation index comprises the following components:
Figure FDA0003200012500000011
wherein, VdIs a dry base volatile component of coal, VvqLower limit of combustible volatile matter required for combustion;
the grindability characteristic Kkm includes the following components when the grindability coefficient is used as an evaluation index:
Figure FDA0003200012500000012
wherein E isbzTo grind the power consumption of standard coal, EsPower consumption for milling test coal;
the ignition characteristic index Z is calculated by:
Figure FDA0003200012500000013
wherein, VadFor volatile content, MadIs the moisture content, CadIs the fixed carbon content;
the calculation formula of the burnout characteristic index F is as follows:
F＝(Vad+Mad)2×Cad×100
wherein, VadFor volatile content, MadIs the moisture content, CadIs the fixed carbon content;
the calculation formula of the flammability characteristic index C is:
Figure FDA0003200012500000014
wherein, VadFor volatile content, MadIs the moisture content, AadIs ash content;
the calculation formula of the stable combustion characteristic index T is as follows:
T＝654-1.9Vad+0.43Aad-4.5Mad
wherein, VadFor volatile content, MadIs the moisture content, AadIs ash content;
the economic efficiency E takes the economic index as an evaluation index, and comprises the following components:
Figure FDA0003200012500000021
wherein: qarLow calorific value, VadThe volatile content, S, J, and G are the sulfur content, coal unit price, and coal freight, respectively;
the pollutant emission I takes an environmental protection score index as an evaluation index, and comprises the following steps:
Figure FDA0003200012500000022
Figure FDA0003200012500000023
wherein: vs1Is SO2Lower limit of emission concentration, Vs2Is SO2Upper limit of discharge concentration, VsIs SO2Discharge concentration, λ1Is SO2Index of failure, Vn1Is NOxLower limit of emission concentration, Vn2Is NOxUpper limit of discharge concentration, VnIs NOxDischarge concentration, λ2Is NOxIndex of failure, Vy1Is the smoke emission concentration, Vy2Lower limit of smoke emission concentration, VyAt the upper limit of the soot emission concentration, λ3Is a smoke fault index, n1Is SO2Number of boiler failures due to increased emissions, n2Is NOxNumber of boiler failures due to increased emissions, n3For the number of boiler faults, n, caused by increased smoke emissionsGThe total number of boiler failures;
the combustion efficiency retrieves data from a system database;
the slagging degree takes the softening temperature of the coal ash as an evaluation index, and the data is collected and selected from the reality;
6) and obtaining a fuzzy comprehensive evaluation result of coal blending and burning through fuzzy transformation according to the fuzzy comprehensive judgment matrix, and determining an optimal coal blending and burning coal quality scheme according to the principle of selecting the maximum membership degree.
2. The fuzzy comprehensive evaluation method for blended coal combustion based on the improved entropy weight method as claimed in claim 1, wherein in the step 1), each evaluation index in the evaluation index set specifically includes a spontaneous combustion characteristic, a grindability characteristic, an ignition characteristic, an ember characteristic, a flammability characteristic, a combustion efficiency, a slagging degree, an economical efficiency, a stable combustion characteristic and a pollutant emission.
3. The fuzzy comprehensive evaluation method for blended coal combustion based on the improved entropy weight method as claimed in claim 1, wherein in the step 2), each decision in the comment set specifically includes excellent, good, medium and poor.
4. The fuzzy comprehensive evaluation method for coal blending combustion based on the improved entropy weight method according to claim 1, wherein the step 3) specifically comprises the following steps:
31) obtaining the importance ranking of each expert on the evaluation index by adopting a Delphi method, and overlapping to form an evaluation index importance ranking matrix A ═ a (a)ij)n×nWherein a isijRanking the number of times of the jth name for the ith index influence degree;
32) determining the weight omega of each evaluation index in the evaluation index set by adopting an improved entropy weight methodi。
5. The fuzzy comprehensive evaluation method for coal blending combustion based on the improved entropy weight method as claimed in claim 4, wherein in the step 32), a membership function H (T) corresponding to an order number T obtained after an expert evaluates an ith evaluation index is taken as an information entropy, and an evaluation index b (T) of a total of m experts on the ith evaluation index is calculated according to a probability f (T) when the order number of the ith evaluation index is TiAnd obtaining the weight omega of each evaluation index after normalizationi。
6. The fuzzy comprehensive evaluation method for coal blending combustion based on the improved entropy weight method according to claim 5, wherein the weight ω of each evaluation index isiThe expression of (a) is:
Figure FDA0003200012500000031
Figure FDA0003200012500000032
Figure FDA0003200012500000033
f(aij)＝bij
wherein, bijIs the ith row and the jth column parameter of the rank membership matrix, n is the total number of evaluation indexes, beta is a constant, and beta is n + 2.
7. The fuzzy comprehensive evaluation method for coal blending combustion based on the improved entropy weight method according to claim 1, wherein in the step 4), in each evaluation index, the smaller the parameters of the stable combustion characteristic and the pollutant emission evaluation index are, the better the corresponding comment is, the smaller the evaluation index is, the better the membership function is, and the following are established:
Figure FDA0003200012500000034
Figure FDA0003200012500000041
Figure FDA0003200012500000042
Figure FDA0003200012500000043
among the evaluation indexes, the larger the evaluation index parameters of the ignition characteristic, the burnout characteristic, the combustible characteristic, the economy, the combustion efficiency, the slagging degree, the grindability characteristic and the spontaneous combustion characteristic are, the better the corresponding comment is, the larger the evaluation index is, the better the membership function is, and the following are found:
Figure FDA0003200012500000044
Figure FDA0003200012500000045
Figure FDA0003200012500000046
Figure FDA0003200012500000051
wherein r is1(x)、r2(x)、r3(x)、r4(x) Respectively representing excellent, good, medium and poor membership functions, wherein x is a specific parameter value of each evaluation index in the coal blending and coal burning scheme to be evaluated, and the parameters a, b, c and d are evaluation index standard values in an evaluation index standard table.
8. The fuzzy comprehensive evaluation method for blended coal combustion based on the improved entropy weight method according to claim 7, wherein the evaluation index standard table specifically comprises:
evaluation index partitioning Is excellent in Good effect Medium and high grade Is poor Self-ignition characteristics ≥2.8 2.1 1.4 ≤1.0 Abradability feature ≥1.5 1.4 1.3 ≤1.2 Ignition characteristics ≥80 60 40 ≤20 Characteristics of burnout ≥2.0 1.5 1.0 ≤0.5 Combustible characteristic ≥2.4 1.9 1.4 ≤0.9 Efficiency of combustion ≥82.5％ 80％ 77.5％ ≤75％ Degree of slag formation ≥1400 1350 1300 ≤1250 Economy of use ≥1.3 1.1 0.9 ≤0.7 Stable combustion characteristic ≤560 585 610 ≥635 Pollutant discharge ≤0.2 0.4 0.6 ≥0.8
。
9. The fuzzy comprehensive evaluation method for coal blending and burning based on the improved entropy weight method as claimed in claim 1, wherein in the step 6), the fuzzy comprehensive evaluation matrix is subjected to fuzzy transformation according to a fuzzy comprehensive judgment matrix to obtain a fuzzy comprehensive evaluation result of coal blending and burning, and the maximum fuzzy comprehensive evaluation value is selected as an optimal coal blending and burning coal quality scheme, specifically:
Figure FDA0003200012500000052
wherein B is a comprehensive judgment matrix, N*For the total number of coal quality schemes for coal blending combustion to be evaluated,
Figure FDA0003200012500000053
is the ith*And (3) carrying out fuzzy comprehensive evaluation on the coal quality blended coal scheme to be evaluated.
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