CN111967721A - Comprehensive energy system greening level evaluation method and system - Google Patents
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Abstract
The invention discloses a comprehensive energy system greening level evaluation method and a system in the technical field of comprehensive energy, and the method comprises the following steps: establishing a comprehensive energy system green evaluation index system, and determining evaluation indexes comprising a plurality of first-level indexes and a plurality of second-level indexes; solving the membership degree of each evaluation index based on a membership degree function; determining the subjective weight of each primary index based on an analytic hierarchy process; determining objective weight of each secondary index based on an entropy weight method; combining the subjective weight of each first-level index and the objective weight of each second-level index, and respectively determining the combined weight of each first-level index and each second-level index; and (4) constructing a fuzzy comprehensive evaluation function by combining the combined weight of each primary index and each secondary index and the membership degree of each evaluation index, performing fuzzy comprehensive evaluation, and determining the greening level of the comprehensive energy system. The systematic evaluation method is provided, the influence of subjective factors and objective factors on the evaluation result is comprehensively considered, the evaluation method is strong in adaptability, and the evaluation result is more objective.
Description
Technical Field
The invention belongs to the technical field of comprehensive energy, and particularly relates to a comprehensive energy system greening level evaluation method and system.
Background
The green level of the comprehensive energy system reflects the environmental benefit of the comprehensive energy system and the evaluation problem thereof. At present, research on comprehensive energy systems mostly focuses on the aspects of system self construction, such as optimized operation, simulation modeling, framework design and the like. A few of documents relate to the discussion of the greening problem of the comprehensive energy system, and most of the documents are also reflected in the extensive application of a single index in the system; the research has poor adaptability on evaluation methods and cannot form a system; the coverage area is narrow on the research content, the connotation exhibition place of the 'green' concept is not sufficient, and the green level of the comprehensive energy system cannot be accurately reflected.
Disclosure of Invention
In order to overcome the defects in the prior art, the invention provides the comprehensive energy system greening level evaluation method and system, provides a systematic evaluation method, comprehensively considers the influence of subjective factors and objective factors on the evaluation result, and has strong adaptability and more objective evaluation result.
In order to achieve the purpose, the technical scheme adopted by the invention is as follows: a green level evaluation method of an integrated energy system comprises the following steps: a. establishing a comprehensive energy system green evaluation index system, and determining evaluation indexes comprising a plurality of first-level indexes and a plurality of second-level indexes; b. solving the membership degree of each evaluation index based on a membership degree function; c. determining the subjective weight of each primary index based on an analytic hierarchy process; d. determining objective weight of each secondary index based on an entropy weight method; e. combining the subjective weight of each first-level index and the objective weight of each second-level index, and respectively determining the combined weight of each first-level index and each second-level index; f. and (4) constructing a fuzzy comprehensive evaluation function by combining the combined weight of each primary index and each secondary index and the membership degree of each evaluation index, performing fuzzy comprehensive evaluation, and determining the greening level of the comprehensive energy system.
Further, the first-level indexes comprise an energy-saving index, a low-carbon index, an environment-friendly index, an emission reduction index and an ecological design index; the energy-saving index comprises two secondary indexes of energy-saving technology popularization utilization rate and energy-saving equipment utilization rate; the low-carbon index comprises two secondary indexes of carbon emission reduction technology coverage rate and carbon market product development rate; the environmental protection indexes comprise two secondary indexes of utilization rate of three-waste treatment technology and recovery utilization rate of emission; the emission reduction indexes comprise two secondary indexes of pollutant emission control technology utilization rate and pollutant statistical technology coverage rate; the ecological design index comprises two secondary indexes of renewable energy utilization rate and resource recycling utilization rate.
Further, the step b specifically includes: b1, constructing an index set; b2, constructing a comment set; b3, selecting a membership function model, and solving the membership of each evaluation index in the index set corresponding to the comment set according to the membership function model.
Further, the step c specifically includes: c1, assigning values to each evaluation index through an expert questionnaire; c2, constructing a first-level judgment matrix according to the assignment of each evaluation index; c3, solving the eigenvector of the first-level judgment matrix and obtaining the subjective weight of each first-level index;
further, the step d specifically includes: d1, constructing a second judgment matrix; d2, determining the information entropy of each evaluation index according to the second judgment matrix; d3, calculating the objective weight of each secondary index according to the information entropy of each evaluation index.
Further, the combination weight of each evaluation index is:
wherein, W** jThe combined weight of the jth secondary index; wiIs the subjective weight of the jth primary index,Uiobjective viewing weight of jth secondary index; m represents the number of secondary indexes.
Further, the fuzzy comprehensive evaluation function is as follows:
B＝A*R (24)
b is the membership degree of the object to be evaluated to the evaluation set; a is a combined weight set; and R is a single index evaluation matrix.
An integrated energy system greening level evaluation system comprises: a first module: the method is used for establishing a comprehensive energy system green evaluation index system and determining an evaluation index; a second module: the evaluation index membership function is used for solving the membership degree of each evaluation index based on the membership degree function; a third module: the subjective weight of each first-level index is determined based on an analytic hierarchy process; a fourth module: the objective weight of each secondary index is determined based on an entropy weight method; a fifth module: the system is used for integrating the subjective weight of each first-level index and the objective weight of each second-level index and respectively determining the combined weight of each first-level index and each second-level index; a sixth module: and the fuzzy comprehensive evaluation function is constructed by combining the combination weight of each primary index and each secondary index and the membership degree of each evaluation index, fuzzy comprehensive evaluation is carried out, and the green level of the comprehensive energy system is determined.
Compared with the prior art, the invention has the following beneficial effects: the invention determines the subjective weight of each index by constructing a hierarchical evaluation index system and combining an analytic hierarchy process, determines the objective weight of each index based on an entropy weight method, further constructs a fuzzy comprehensive evaluation function to determine the greening level of a comprehensive energy system, provides a systematic evaluation method, converts complex and fuzzy concept description and empirical data into a mathematical analysis result with higher quantization precision, and is beneficial to solving a multi-objective decision problem. The method comprehensively considers the influence of subjective and objective factors on the evaluation result, and has strong adaptability and more objective evaluation result.
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Fig. 1 is a flowchart of an evaluation method for greenness level of an integrated energy system according to an embodiment of the present invention;
fig. 2 is an evaluation index system of the comprehensive energy system greening level evaluation method provided by the embodiment of the invention;
Detailed Description
The invention is further described below with reference to the accompanying drawings. The following examples are only for illustrating the technical solutions of the present invention more clearly, and the protection scope of the present invention is not limited thereby.
The first embodiment is as follows:
as shown in fig. 1, a method for evaluating the greening level of an integrated energy system includes: a. establishing a comprehensive energy system green evaluation index system, and determining evaluation indexes comprising a plurality of first-level indexes and a plurality of second-level indexes; b. solving the membership degree of each evaluation index based on a membership degree function; c. determining the subjective weight of each primary index based on an analytic hierarchy process; d. determining objective weight of each secondary index based on an entropy weight method; e. combining the subjective weight of each first-level index and the objective weight of each second-level index, and respectively determining the combined weight of each first-level index and each second-level index; f. and (4) constructing a fuzzy comprehensive evaluation function by combining the combined weight of each primary index and each secondary index and the membership degree of each evaluation index, performing fuzzy comprehensive evaluation, and determining the greening level of the comprehensive energy system.
1. Establishing a comprehensive energy system green evaluation index system, and determining evaluation indexes
As shown in fig. 2, based on the green operation of the integrated energy system, the evaluation indexes are divided into five primary indexes: energy conservation, low carbon, environmental protection, emission reduction and ecological design. The energy-saving index consists of two secondary indexes of energy-saving technology popularization utilization rate and energy-saving equipment utilization rate; the low-carbon index consists of two secondary indexes, namely carbon emission reduction technology coverage rate and carbon market product development rate; the environmental protection index consists of two secondary indexes of three-waste treatment technology utilization rate and emission recovery utilization rate; the emission reduction index consists of two secondary indexes, namely the utilization rate of a pollutant control technology and the coverage rate of a pollutant statistical technology; the ecological design index consists of two secondary indexes of renewable energy utilization rate and resource recycling utilization rate.
For each secondary index, the analysis was as follows:
1) popularization and utilization rate of energy-saving technology
The popularization and use rate of the energy-saving technology refers to the coverage percentage of the energy-saving technology application in all working units related to energy generation, transportation and use in the system, and is calculated by using a formula (1):
wherein A is11The popularization and use rate of the energy-saving technology is high; q1The number of working units applying the energy-saving technology in the system is Q, and the total number of all the working units related to the processes of energy transmission, distribution, delivery and use in the system is Q; the working unit can be identified according to different existing states of the energy in the system operation process;
2) utilization of energy saving equipment
The utilization rate of the energy-saving equipment is an index reflecting the working state of the energy-saving equipment in the system, generally refers to the percentage of actual use time of each year to planned time, and can be calculated by a formula (2):
wherein A is12The utilization rate of energy-saving equipment; q. q.s1The number of the starting-up devices of the energy-saving equipment in the system at a certain sampling moment, and q is the total number of all the energy-saving equipment configured in the system;
3) carbon reduction technology coverage
The carbon emission reduction technology in the comprehensive energy system mainly comprises the following steps: source emission reduction (such as screening and using of clean energy sources) process emission reduction (such as optimized operation of a natural gas unit) and result emission reduction (such as capture, sequestration and conversion of carbon dioxide). The carbon emission reduction technology coverage rate is the percentage of the number of working units using the carbon emission reduction technology to the total number of all working units related to carbon dioxide emission in the system, and can be calculated by formula (3):
wherein A is21Is carbon emission reduction technology coverage; p1Is the number of working units using carbon emission reduction technology, and P is the total number of all working units in the system involved in the carbon dioxide emission process; the working unit can be identified according to different existing states of the energy in the system operation process;
4) carbon market product development rate
The development of carbon market products in integrated energy systems generally includes two categories: carbon market products in a narrow sense (such as voluntary emission reduction mechanism and carbon general mechanism items) and carbon market products in a broad sense (such as green certificate trading, energy saving trading, energy right trading and the like); the trade target of the latter can be converted into carbon dioxide emission reduction, and further forms a unified carbon market with the former. The carbon market product development rate is the percentage of all certified carbon dioxide emission reductions (including the conversion) generated by the carbon market project to the total emission reduction of carbon dioxide generated in the system, and can be calculated by the formula (4):
wherein A is22Is the carbon market product development rate; p is a radical of1Is all the nuclear evidence carbon dioxide emission reduction produced by carbon market development; p is a radical of2Carbon dioxide emission reduction volume generated within a system and not certified by a certification authority
5) Utilization rate of three wastes treatment technology
The three-waste treatment technology mentioned here mainly refers to the technology of environmental protection end treatment for waste water, waste gas and waste slag generated by system operation. The utilization rate of the three-waste treatment technology refers to the percentage of the amount of the industrial three wastes treated by the environmental protection technology to the total amount of the industrial three wastes generated by the operation of the system, and can be calculated by a formula (5):
wherein A is31The utilization rate of the three-waste treatment technology is high; m1Is the amount of industrial three wastes treated by the environmental protection technology; m2Is the amount of industrial three wastes generated by system operation and not treated by an environmental protection technology;
6) emission recycle
The emission recovery utilization rate is the percentage of the environmental pollutant discharge amount recovered, recycled or converted by a technical and management means to the total environmental pollutant discharge amount generated by the system operation, and can be calculated by the formula (6):
wherein A is32Is the effluent recycle; m is1Is the discharge amount of the recycled, recycled or converted environmental pollutants; m is2The total discharge amount of environmental pollutants generated by system operation;
7) rate of utilization of pollutant control technology
Pollutant emission front-end control techniques generally involve process flow modifications and optimal selection of raw materials. The pollutant control technology utilization rate is the percentage of the number of working units adopting the pollutant control technology to the total number of all working units related to pollutant emission, and can be calculated by the formula (7):
wherein A is41Is the rate of utilization of the pollutant control technology, N1Is the number of working units, N, using a contaminant control technique2Is the number of other work units within the system that are involved in pollutant emissions and that do not implement emission control techniques;
8) pollutant statistics technology coverage rate
Pollutant statistics technologies generally include pollution source census and analysis, atmospheric pollutant source analysis technology, atmospheric pollutant source list compilation, continuous tracking and monitoring of heavy pollution sources, and the like. The pollutant statistical technology coverage rate is the percentage of the number of monitored, general survey and counted pollution sources in the total number of the pollution sources in the region constructed and operated by the comprehensive energy system, and can be calculated by a formula (8):
wherein A is42Is the pollutant statistics technique coverage, n1The number of pollution sources, n, listed in the system for monitoring, general survey and statistics2The total number of pollution sources which are not listed in the monitoring, census and statistics in the area where the system is located;
9) utilization rate of renewable energy
With respect to renewable energy utilization, different application scenarios have different definitions. The utilization rate of the renewable energy sources mentioned in the invention is the percentage of the utilization amount of the renewable energy sources in the system to the total energy consumption in the system; can be calculated using equation (9):
wherein A is51The method refers to the utilization rate of renewable energy sources; k1The value is the annual renewable energy utilization amount in the system, and the value can be uniformly converted into standard coal amount for calculation by adopting an equivalent electrical method according to different energy grades; k2The total energy consumption of the system is referred to, and the value can be converted into standard coal quantity for calculation;
10) cyclic utilization of resources
Regarding the concept of resource cyclic utilization, no unified and authoritative definition exists at present; the resource cyclic utilization rate mainly refers to the recycling utilization rate of the regenerated resources including the abandoned electromechanical equipment in the system operation process, and can be calculated by a formula (10):
wherein A is52Means resource cyclic utilization; k is a radical of1The amount of the recycled resources recovered and reused by technical measures is referred to; k is a radical of2Refers to the total amount of all resources wasted during the operation of the system.
2. Membership degree of each evaluation index is obtained based on membership degree function
1) Constructing an index set: the first-level index u in the index system1、u2、u3、u4、u5Form a first-level index set U ═ U1，u2，u3，u4，u5}; each first-level index comprises two second-level indexes which can form a second-level index set (first-level index u)1The corresponding secondary index is u11，u12First order index u2The corresponding secondary index is u21，u22First order index u3The corresponding secondary index is u31，u32First order index u4The corresponding secondary index is u41，u42First order index u5The corresponding secondary index is u51，u52B), namely a secondary index set U1＝{u11，u12}，U2＝{u21，u22}，U3＝{u31，u32}，U4＝{u41，u42}，U5＝{u51，u52}。
2) Establishing a comment set, and establishing a comment set V ═ V { according to the characteristics of the evaluated comprehensive energy system1，v2，v3，v4And establishing a comment set V which corresponds to four evaluation levels, wherein the comment set V is good, general and poor.
3) Selecting a membership function model, and solving the membership of each primary index in the primary index set and each secondary index in each secondary index set corresponding to the comment set according to the membership function model;
and selecting an expert experience method for the membership function establishment method. A plurality of experts give different evaluation levels to the comprehensive energy system according to experience; the proportion of the experts under each evaluation level forms a comment weight collection coefficient; according to the weight coefficient of the comment set, a membership function can be preliminarily determined, and according to the membership function relationship, the membership of each evaluation index to the comment set can be obtained;
in terms of membership function model, the invention selects a normal distribution, namely:
wherein T (x) is a membership value, x is an actual value of each evaluation index in the index set, a is a first parameter of a membership function and represents a standard deviation of an expected value, and b is a second parameter of the membership function and represents a standard deviation of an expected value
The standard deviation of the fold, the selection of a and b values, can be obtained by fitting with the least square method.
3. Subjective weight determination of each primary index based on analytic hierarchy process
Determining a weight set, establishing a first level weight set corresponding to the first level index set and a second level weight set corresponding to the second level index set:
first level weight set a ═ a1，a2，a3，a4，a5) (ii) a Wherein, a1～a5Represents the weight assigned according to the relative importance of each primary index in the overall evaluation system.
Second level weight set A1＝(a11，a12)，A2＝(a21，a22)，A3＝(a31，a32)，A4＝(a41，a42)，A5＝(a51，a52) (ii) a Wherein, a12Representing the weight given according to the comparison result of the importance degree of the 1 st secondary index relative to the 2 nd secondary index in the overall evaluation system; in the same way, canOther elements in the second hierarchical weight set are defined.
Determining subjective weight of each evaluation index based on an analytic hierarchy process (AHP method): carrying out hierarchical classification on the influence factors for solving the actual problems to obtain a hierarchical structure; it generally consists of three levels: target layer: how to judge the influence of each factor on the green color of the comprehensive energy system; a criterion layer: factors influencing greenness of the comprehensive energy system and composition criteria thereof; scheme layer: according to the analysis result, the green performance of the comprehensive energy system can be improved by adopting a decision scheme; the subjective weight is determined by an AHP method, and the problem of the relative weight of each factor to a target layer is mainly researched.
1) And (3) assigning each evaluation index through an expert questionnaire:
sending a grading questionnaire to related experts, and preliminarily determining U, U indexes of the experts1～U5And (4) judging the influence degree of each evaluation index on the greenness of the comprehensive energy system.
The principle of expert scoring is as follows:
inviting experts to make pairwise comparison between indexes, if the experts consider index ImRatio index InIf the number is important, filling a plus sign in the corresponding table, and recording the percentage of the experts as G;
if the two are considered as equally important, filling a mark, and recording the percentage of the part of experts as E;
if it is considered to be ImIs less than index InIf the number is important, filling a minus number, and recording the percentage of the part of experts as S;
assigning values to the indexes according to the mapping rules of the table 1 by taking the value of (G-S) as a standard for establishing mapping; if the value of (G-S) is a negative value, carrying out corresponding assignment on the value according to 1/9-1;
TABLE 1G-S based mapping rules
| G-S value | 0 | 10％～ | 20％～ | 30％～ | 40％～ | 50％～ | 60％～ | 70％～ | 80％～ |
| Assignment of value | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
Based on the principle of expert scoring, finally obtaining index sets U and U1～U5Assigning values after comparing every two evaluation indexes;
2) constructing a first level judgment matrix:
constructing a first hierarchy based on the value assignment for each evaluation indexJudgment matrix Z*It can be expressed as:
wherein, a* 12The evaluation method comprises the steps of representing assignment of a comparison result of a first primary index relative to a second primary index according to the mapping principle when subjective weight is determined by adopting an analytic hierarchy process; by the same token, a matrix Z can be given*The definition of the other elements in (a).
3) Calculating a weight coefficient of an index
And calculating the weight coefficient of each primary index by using a characteristic root method to obtain the subjective weight of each evaluation index.
First, a first-level judgment matrix Z is calculated*The hierarchical single ordering of (1):
wherein, I is a natural number and represents the row number of the matrix; here, I is 1,2,3,4, 5; j is a natural number and represents the column number j of the matrix to be 1,2 …, m; n is the order of the first-level decision matrix, a* ijDetermining the matrix Z for the first level*According to the relative importance degree, after the I first-level index is compared with the j first-level index, the value is assigned according to the mapping rule;
is the n-th root of the row I element product.
Then, according to the formula (14), for
Normalization processing is carried out to obtain the subjective weight W of the I index* i：
Further obtain matrix Z*Characteristic vector W of*＝[W* 1，W* 2，W* 3，W* 4,W* 5]Wherein W is* 1～W* 5The subjective weighted value corresponding to each first-level index;
4) first-level judgment matrix Z*The consistency test of (2):
to check W*Whether the weight distribution is reasonable or not needs to be checked for consistency of the first-level judgment matrix:
firstly, the maximum eigenvalue lambda of a first level judgment matrix is calculatedmax：
Wherein (Z)*W*)IIs a vector Z*W*The I component, W* IIs the subjective weight of the first level indicator;
and secondly, introducing a consistency index CI to measure the degree of deviation of the first-level judgment matrix from consistency.
Third, a consistency ratio CR is calculated
Wherein, RI is an average random consistency index, and can be obtained by a first-level decision matrix order lookup table (table 2);
TABLE 2 average random consistency index RI values
| First-level judgment matrix order | 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 |
| Assignment of value | 0.00 | 0.00 | 0.58 | 0.90 | 1.12 | 1.24 | 1.32 | 1.41 | 1.46 |
Through calculation, when CR is less than 0.1, the first-level judgment matrix meets the requirement of consistency, otherwise, each index needs to be assigned again.
4. Determining objective weight and combined weight of each secondary index based on entropy weight method
In this embodiment, an entropy weight method is used to determine the objective weight of each secondary index:
1) constructing a second-level judgment matrix;
Z**＝(zij)t╳m (19)
wherein, Z represents a second level judgment matrix; z is a radical ofijExpressing the jth secondary index in the ith comprehensive energy system to be evaluated in the second-level judgment matrix; t represents the number of the comprehensive energy systems to be evaluated; m represents the number of secondary indexes;
2) and (3) carrying out normalization processing on the data:
wherein z is* ijIs zijThe index value after normalization;
3) determining the information entropy of each evaluation index;
wherein S is* jIs the information entropy of the jth secondary index, when z* ijWhen equal to 0, let z* ijln(z* ij)＝0；
4) Calculating the weight of each index through the information entropy:
wherein Q is* jEntropy weight of the jth secondary index;
finally, a secondary index weight vector U based on an entropy weight method is obtained*，U*＝(U1，U2，…Un) The objective weight value corresponding to each secondary index is obtained.
And (3) integrating the subjective weight and the objective weight of each evaluation index to determine the combined weight of each secondary index: the results of the analytic hierarchy process and the entropy weight process are integrated to obtain the combined weight considering both subjective and objective factors,
wherein, W** jThe combined weight of the jth secondary index; wiSubjective weight, U, of the jth primary indexiObjective viewing weight of jth secondary index; multiple combining weights W** jCan form a weight set AjAnd the method is used for fuzzy evaluation of the indexes. Similarly, the combined weight of each level of indicators can be determined.
5. Constructing a fuzzy comprehensive evaluation function and carrying out fuzzy comprehensive evaluation
And (3) constructing a fuzzy comprehensive evaluation function by combining the combination weight of each evaluation index and the membership degree of each evaluation index, performing fuzzy comprehensive evaluation, and determining the greening level of the comprehensive energy system:
1) construction of fuzzy comprehensive evaluation function
Considering the influence of various factors on the evaluation object, a fuzzy comprehensive evaluation function can be established:
B＝A*R； (24)
b is the membership degree of the object to be evaluated to the evaluation set, is a comprehensive evaluation index, and when the meaning of the comprehensive evaluation index represents multiple factors, the membership degree of the object to be evaluated (comprehensive energy system greening attribute) to the evaluation set; a is a first hierarchical weight set, which may be expressed as a ═ a (a)1,a2,a3,a4,a5)；
R is a single index evaluation matrix, and the meaning of the matrix is as follows: the I line reflects the membership degree of the j index to all elements in the comment set; the jth column reflects the degree of membership of all the indicators to a certain element in the comment set. R can be represented as:
wherein r isIjRepresenting the membership degree of the indexes of the I row and the j column to the comment set in the single index matrix;
then, the fuzzy synthetic merit function may be expressed as:
the operation symbol in the formula (26) is expressed by various models in mathematics, and the selection method of the symbol in the fuzzy comprehensive evaluation of the embodiment operates according to the following models, corresponding to different operation modes:
wherein, M (·, V) represents that the model adopts common multiplication and carries out a large operation; bjA fuzzy comprehensive evaluation function representing a j-th column; a isIA weight representing the I index; r isijRepresenting the membership degree of the indexes of the I row and the j column to the comment set in the single index matrix; m is a natural number.
Because the two-stage index system involved in the invention needs to carry out two-stage evaluation according to the definition of the fuzzy comprehensive evaluation function.
2) First-level fuzzy comprehensive evaluation
And (3) taking the secondary indexes in the index system as objects, and inspecting the membership degree of each secondary index to the comment set, wherein the evaluation is called primary fuzzy comprehensive evaluation.
Setting the I index u of the evaluation object in the secondary index setICarrying out fuzzy evaluation to j element v in evaluation setjDegree of membership of, denoted as rIjAccording to the I < th > index uIThe single index evaluation matrix for evaluation can be recorded as: rI＝(rI1,rI2,…,rIj) (I ═ 1,2, …, m; m is a natural number); similarly, each single index evaluation matrix evaluated according to other indexes can be obtained in sequence.
Then, the single index evaluation matrix in each secondary index is used as a row to form a matrix R* IFurther, the first-level fuzzy comprehensive evaluation is carried out,
wherein R is* IA single index evaluation matrix for primary fuzzy comprehensive evaluation; r isIjRepresenting the membership degree of the indexes of the I row and the j column to the comment set in the single index matrix; i represents the number of rows and j represents the number of columns;
after the combined weight set A is considered, a first-level fuzzy comprehensive evaluation index B is obtained* ICan be expressed as:
wherein, (j ═ 1,2, …, m); a. the* IThe combined weight set is obtained by combining weight calculation results according to the AHP and the entropy weight method.
3) Two-stage fuzzy evaluation
The first-level fuzzy comprehensive evaluation result, namely the first-level fuzzy comprehensive evaluation index B* IConstructing a new matrix R as an input element**Inspecting a first-level index in an index system, and performing single-index evaluation on the membership degree of each element in the evaluation set, wherein the single-index evaluation is called second-level fuzzy comprehensive evaluation;
single index judgment matrix R in secondary comprehensive fuzzy judgment**Can be expressed as:
then, the calculation of the secondary fuzzy comprehensive evaluation index (evaluation function) is as follows:
B**＝A***R** (31)
wherein A is**The combined weight set is obtained by combining weight calculation results according to the AHP and the entropy weight method.
4) Processing method for comprehensive fuzzy comprehensive evaluation index B
The evaluation result can be determined by combining the following two methods:
the maximum membership method comprises the following steps: if B isI＝max{BjAnd (j ═ 1, 2.. times, m), the index B is judgedIBelonging to a certain element v of the set of wordsI(ii) a Wherein, BIRepresenting the degree of membership of the I-th object to be evaluated, BjRepresenting the membership degree of the jth index in all evaluated objects; i denotes the number of samples and j denotes the number of indices.
F, distribution method: to Bj(j is 1,2,.. said.m, m is a natural number) and normalizing the values so that
The fuzzy comprehensive evaluation index B obtained under the condition*Can be represented as;
in the formula (30)
The value of (b) reflects the distribution of the evaluation target (integrated energy system) in the evaluation characteristics (degree of greening), i.e., the percentage of different elements in the evaluation set.
5) Fuzzy comprehensive evaluation result analysis
According to the processing result of the fuzzy comprehensive evaluation index B by the maximum membership method and the F analysis method, the greening levels of different comprehensive energy systems can be determined, and the distribution condition of the membership degree in the evaluation set can be determined.
The evaluation method for the distribution of the greening attributes of the comprehensive energy system on different levels according to the differences of different index evaluation results can give consideration to the characteristics of subjective and objective weights, overcomes the uncertainty and ambiguity of greening level evaluation, and can provide new research ideas and technical routes for the aspects of judgment of greening degree, enrichment of a greening index system, analysis of environmental benefits and the like of the future comprehensive energy system.
Example two:
based on the first method for evaluating the greening level of the integrated energy system in the embodiment, the present embodiment provides a system for evaluating the greening level of the integrated energy system, which includes: a first module: the method is used for establishing a comprehensive energy system green evaluation index system and determining an evaluation index; a second module: the evaluation index membership function is used for solving the membership degree of each evaluation index based on the membership degree function; a third module: the subjective weight of each first-level index is determined based on an analytic hierarchy process; a fourth module: the objective weight of each secondary index is determined based on an entropy weight method; a fifth module: the system is used for integrating the subjective weight of each first-level index and the objective weight of each second-level index and respectively determining the combined weight of each first-level index and each second-level index; a sixth module: and the fuzzy comprehensive evaluation function is constructed by combining the combination weight of each primary index and each secondary index and the membership degree of each evaluation index, fuzzy comprehensive evaluation is carried out, and the green level of the comprehensive energy system is determined.
The above description is only a preferred embodiment of the present invention, and it should be noted that, for those skilled in the art, several modifications and variations can be made without departing from the technical principle of the present invention, and these modifications and variations should also be regarded as the protection scope of the present invention.
Claims (8)
1. A green level evaluation method of a comprehensive energy system is characterized by comprising the following steps:
a. establishing a comprehensive energy system green evaluation index system, and determining evaluation indexes comprising a plurality of first-level indexes and a plurality of second-level indexes;
b. solving the membership degree of each evaluation index based on a membership degree function;
c. determining the subjective weight of each primary index based on an analytic hierarchy process;
d. determining objective weight of each secondary index based on an entropy weight method;
e. combining the subjective weight of each first-level index and the objective weight of each second-level index, and respectively determining the combined weight of each first-level index and each second-level index;
f. and (4) constructing a fuzzy comprehensive evaluation function by combining the combined weight of each primary index and each secondary index and the membership degree of each evaluation index, performing fuzzy comprehensive evaluation, and determining the greening level of the comprehensive energy system.
2. The integrated energy system greening level evaluation method according to claim 1, wherein the primary indexes include an energy saving index, a low carbon index, an environmental protection index, an emission reduction index and an ecological design index; the energy-saving index comprises two secondary indexes of energy-saving technology popularization utilization rate and energy-saving equipment utilization rate; the low-carbon index comprises two secondary indexes of carbon emission reduction technology coverage rate and carbon market product development rate; the environmental protection indexes comprise two secondary indexes of utilization rate of three-waste treatment technology and recovery utilization rate of emission; the emission reduction indexes comprise two secondary indexes of pollutant emission control technology utilization rate and pollutant statistical technology coverage rate; the ecological design index comprises two secondary indexes of renewable energy utilization rate and resource recycling utilization rate.
3. The method for evaluating the integrated energy system greening level according to claim 1, wherein the step b specifically comprises the following steps:
b1, constructing an index set;
b2, constructing a comment set;
b3, selecting a membership function model, and solving the membership of each evaluation index in the index set corresponding to the comment set according to the membership function model.
4. The method for evaluating the integrated energy system greening level according to claim 1, wherein the step c specifically comprises the following steps:
c1, assigning values to each evaluation index through an expert questionnaire;
c2, constructing a first-level judgment matrix according to the assignment of each evaluation index;
and c3, obtaining the eigenvector of the first-level judgment matrix and obtaining the subjective weight of each first-level index.
5. The method for evaluating the integrated energy system greening level according to claim 1, wherein the step d specifically comprises the following steps:
d1, constructing a second judgment matrix;
d2, determining the information entropy of each evaluation index according to the second judgment matrix;
d3, calculating the objective weight of each secondary index according to the information entropy of each evaluation index.
6. The method for evaluating the greening level of the integrated energy system according to claim 1, wherein the combination weight of each evaluation index is as follows:
wherein, W** jThe combined weight of the jth secondary index; wiSubjective weight, U, of the jth primary indexiObjective viewing weight of jth secondary index; m represents the number of secondary indexes.
7. The method according to claim 1, wherein the fuzzy comprehensive evaluation function is:
B＝A*R (24)
b is the membership degree of the object to be evaluated to the evaluation set; a is a combined weight set; and R is a single index evaluation matrix.
8. A comprehensive energy system greening level evaluation system is characterized by comprising:
a first module: the method is used for establishing a comprehensive energy system green evaluation index system and determining an evaluation index;
a second module: the evaluation index membership function is used for solving the membership degree of each evaluation index based on the membership degree function;
a third module: the subjective weight of each first-level index is determined based on an analytic hierarchy process;
a fourth module: the objective weight of each secondary index is determined based on an entropy weight method;
a fifth module: the system is used for integrating the subjective weight of each first-level index and the objective weight of each second-level index and respectively determining the combined weight of each first-level index and each second-level index;
a sixth module: and the fuzzy comprehensive evaluation function is constructed by combining the combination weight of each primary index and each secondary index and the membership degree of each evaluation index, fuzzy comprehensive evaluation is carried out, and the green level of the comprehensive energy system is determined.
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