CN109146123A - A kind of multiple-energy-source comprehensive coordination effect evaluation method and system - Google Patents
A kind of multiple-energy-source comprehensive coordination effect evaluation method and system Download PDFInfo
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Abstract
The present invention provides a kind of multiple-energy-source comprehensive coordination effect evaluation method and systems, it include: that Triangular Fuzzy Number significance level evaluation result between each same level factor of effect multi-layer appraisement system is synthesized and coordinated based on the multiple-energy-source that pre-establishes, the weight of each factor in Calculation Estimation system；Based on the marking to factor in appraisement system as a result, obtaining evaluations matrix；According to weight and evaluations matrix, the evaluation result of Calculation Estimation system.This method and system calculate the weight of each factor in the appraisement system by the Triangular Fuzzy Number significance level evaluation result that multiple-energy-source synthesizes and coordinates effect multi-layer appraisement system, marking result based on factor in the appraisement system, obtain evaluations matrix, finally according to weight and evaluations matrix, the evaluation result of Calculation Estimation system, effect can be coordinated and optimized from multiple-energy-source, multiple-energy-source coordination optimization operation is evaluated, can be used for evaluating energy Internet Engineering.
Description
Technical field
The invention belongs to energy Internet technical fields, and in particular to a kind of multiple-energy-source comprehensive coordination effect evaluation method and
System.
Background technique
Fast development of the electric power as one of most important energy field, especially intelligent power grid technology, will become in the energy
It plays a significant role in leather.With the continuous propulsion of " internet+" theory, it is by the energy internet of core of active distribution network
Traditional energy industry proposes the new route and new concept of development.Compared to traditional power grid, various energy resources are more emphasized in energy internet
Integrated complementary utilizes between form, coordination optimization is run, and is that raising power grid is horizontal to the consumption of distributed energy, accelerates clean energy resource
Substitution, lifting region energy supply comprehensive energy efficiency, realize " low-carbon, economy, safe, high-quality " operation mesh of region energy supplying system
Target important channel.Currently, power grid of the evaluation of electric network synthetic operation mainly for the single energy, it is difficult to meet mutual towards the energy
The requirement for multiple-energy-source coordination optimization operation Comprehensive Assessment Technology of networking.Existing active distribution network multipotency Coordination Evaluation factor in a steady stream
System does not account for the complementary coordination benefit between the multiple power sources such as the various energy resources such as hot and cold, gas and wind-powered electricity generation, photovoltaic, selects in factor
Take scientific, polymerization reasonability etc. cannot reflecting regional energy internet comprehensively safe operation, coordination optimization and economy
Benefit.
Summary of the invention
To overcome the multiple-energy-source coordination optimization operation synthesis of the above-mentioned prior art being difficult to meet towards energy internet to comment
The deficiency of valence, the present invention propose that a kind of multiple-energy-source synthesizes and coordinates effect evaluation method and system.This method and system can be by grinding
Study carefully the multi-source coordination optimization operation Comprehensive Assessment Technology towards energy internet, proposes that Regional Energy internet multi-source optimizes efficiency
Evaluation quantization analysis method is realized and carries out overall merit to Regional Energy internet multi-source optimization operational effect, can enrich more
The theory and technology basis of efficiency evaluation is coordinated in source, provides judgment basis for the reasonable operation of following Regional Energy internet.Meanwhile
Multi-source, which coordinates efficiency evaluation result, can feed back to multi-source coordination optimization system, and multi-source coordination optimization system is instructed reasonably to be adjusted
It is whole, realize the energy it is efficient utilize, increase system is to the digestion capability of clean energy resource, promote energy-consuming to clean.Meanwhile it is logical
The theoretical research of project is crossed, can learn to improve advanced research theory and Comprehensive Assessment Technology, a collection of energy internet can be turned out
Highly qualified specialist, academic backbone and the young academic backbone that assay field basis is sturdy, has the very strong capacity of scientific research, to future
Support and leading action are played in the development of energy Internet technology.
Realize solution used by above-mentioned purpose are as follows:
A kind of multiple-energy-source comprehensive coordination effect evaluation method, thes improvement is that:
The Triangle Module between each same level factor of effect multi-layer appraisement system is synthesized and coordinated based on the multiple-energy-source pre-established
Number significance level evaluation result is pasted, the weight of each factor in the appraisement system is calculated；
Based on the marking to factor in the appraisement system as a result, obtaining evaluations matrix；
According to the weight and the evaluations matrix, the evaluation result of the appraisement system is calculated.
First optimal technical scheme provided by the invention, it is improved in that described based on the multiple-energy-source pre-established
The Triangular Fuzzy Number significance level evaluation result between each same level factor of effect multi-layer appraisement system is synthesized and coordinated, described in calculating
The weight of each factor in appraisement system, comprising:
The triangle of three parameters is used between multiple-energy-source comprehensive coordination each same level factor of effect multi-layer appraisement system
Fuzzy number carries out significance level judge；
Based on the significance level evaluation result, each factor is calculated in the appraisement system with respect to same level other factors
Synthesis significance level；
According to the comprehensive significance level, the weight of each level factor in the appraisement system is calculated.
Second optimal technical scheme provided by the invention, it is improved in that described judged based on the significance level
It is shown below as a result, calculating each factor in the appraisement system with respect to the synthesis significance level of same level other factors:
Wherein, DiFor factor i with respect to same level other factors synthesis importance value, n be factor i where level because
The total number of element, aij indicate the Triangular Fuzzy Number significance level evaluation result between factor i and same level factor j,WithRespectively Triangular Fuzzy Number aijThree parameters.
Third optimal technical scheme provided by the invention, it is improved in that it is described according to the comprehensive significance level,
The weight for calculating each level factor in the appraisement system, is shown below:
Wj'=v (Dj≥D1,D2,…,Dn)=min v (Dj≥Di), i=1,2 ..., n, i ≠ j
Wherein, wjThe weight of j-th of factor of ' expression, DjThe synthesis significance level of expression factor j, DiExpression factor i's is comprehensive
Close significance level, v (Dj≥D1,D2,…,Dn) indicate DjMore than or equal to the possibility of the comprehensive significance level of same level other factors
Degree, v (Dj≥Di) indicate Dj≥DiPossibility degree, v (Dj≥Di) such as following formula calculating:
Wherein,WithRespectively Triangular Fuzzy Number DjThree parameters,WithRespectively triangle is fuzzy
Number DiThree parameters.
4th optimal technical scheme provided by the invention, it is improved in that give a mark to factor in the appraisement system,
Including giving a mark to factor in the appraisement system to the degree of membership of each evaluation approach.
5th optimal technical scheme provided by the invention, it is improved in that described according to the weight and institute's commentary
Valence matrix calculates the evaluation result of the appraisement system, comprising:
Fuzzy composition operation is carried out using the weight and evaluations matrix, obtains Comprehensive Evaluation vector；
According to the Comprehensive Evaluation vector, the appraisement system is obtained to the degree of membership of each evaluation approach；
Evaluation result is determined according to the degree of membership of each evaluation approach.
6th optimal technical scheme provided by the invention, it is improved in that described use the evaluations matrix and power
Weight matrix carries out fuzzy composition operation, obtains Comprehensive Evaluation vector, comprising:
If carrying out the evaluation of bottom set of factors, fuzzy conjunction is carried out using the corresponding evaluations matrix of bottom set of factors and weight
At operation, the corresponding Comprehensive Evaluation vector of bottom set of factors is obtained；
Otherwise, acquisition carries out the corresponding Comprehensive Evaluation vector of lower layer factors collection of factor of evaluation collection, obtain carrying out evaluation because
Element collects corresponding evaluations matrix, carries out fuzzy composition fortune using the corresponding evaluations matrix of the progress factor of evaluation collection and weight
It calculates, obtains carrying out the corresponding Comprehensive Evaluation vector of factor of evaluation collection.
7th optimal technical scheme provided by the invention, it is improved in that described corresponding using bottom set of factors
Evaluations matrix and weight carry out fuzzy composition operation, obtain the corresponding Comprehensive Evaluation vector of bottom set of factors, are shown below:
Wherein, B indicates that the corresponding Comprehensive Evaluation vector of the appraisement system bottom factor, W indicate that bottom set of factors is corresponding
Weight, R indicates the corresponding evaluations matrix of bottom factor,Indicate Fuzzy Arithmetic Operators.
8th optimal technical scheme provided by the invention, it is improved in that the acquisition carries out factor of evaluation collection
The corresponding Comprehensive Evaluation vector of lower layer factors collection is obtained carrying out the corresponding evaluations matrix of factor of evaluation collection, is shown below:
Wherein, C indicates the corresponding evaluations matrix of carry out factor of evaluation collection other than bottom, B1..., BnRespectively indicate progress
The corresponding Comprehensive Evaluation vector of each lower layer factors collection of factor of evaluation collection.
9th optimal technical scheme provided by the invention, it is improved in that described use the carry out factor of evaluation
Collect corresponding evaluations matrix and weight carries out fuzzy composition operation, obtains progress factor of evaluation collection and correspond to Comprehensive Evaluation vector, such as
Shown in following formula:
Wherein, B ' indicates that the corresponding Comprehensive Evaluation vector of the carry out factor of evaluation collection other than bottom, W ' indicate bottom
The corresponding weight of the carry out factor of evaluation collection in addition,Indicate Fuzzy Arithmetic Operators.
Tenth optimal technical scheme provided by the invention, it is improved in that it is described according to the Comprehensive Evaluation vector,
The appraisement system is obtained to the degree of membership of each evaluation approach, comprising:
Respectively using each component of the Comprehensive Evaluation vector as the degree of membership of the corresponding evaluation approach of the component.
11st optimal technical scheme provided by the invention, it is improved in that the multiple-energy-source synthesizes and coordinates effect
The factor of evaluation of multi-layer appraisement system includes:
Safe operation, coordination optimization, economic benefit and social benefit；
The safe operation includes: that supply voltage qualification rate, power supply reliability, three-phase load unbalance degree and electric current are humorous
Wave aberration rate；
The coordination optimization includes: renewable energy acceptance, various energy resources mutual benefit and replacement benefit, peak-valley difference variation and sets
Standby utilization rate；
The economic benefit includes: that equipment investment reduces percentage, operation maintenance cost reduces percentage, line loss per unit reduces
Percentage and Custom interruption cost reduce percentage；
The social benefit includes: electric energy substitution emission reduction change rate, power generation emission reduction change rate and ten thousand yuan of output value energy consumptions
Change rate.
A kind of multiple-energy-source comprehensive coordination effect evaluation system, it is improved in that including weight module, evaluations matrix mould
Block and evaluation computing module；
The weight module, for synthesizing and coordinating each same layer of effect multi-layer appraisement system based on the multiple-energy-source pre-established
Triangular Fuzzy Number significance level evaluation result between grade factor, calculates the weight of each factor in the appraisement system；
The evaluations matrix module, for based on the marking to factor in the appraisement system as a result, obtaining evaluations matrix；
The evaluation computing module, for calculating commenting for the appraisement system according to the weight and the evaluations matrix
Valence result.
12nd optimal technical scheme provided by the invention, it is improved in that the weight module includes: comprehensive weight
Want degree unit and weight unit；
The comprehensive significance level unit calculates in the appraisement system for being based on the significance level evaluation result
Synthesis significance level of each factor with respect to same level other factors；
The weight unit, for calculating each level factor in the appraisement system according to the comprehensive significance level
Weight；
Wherein, three parameters are used between multiple-energy-source comprehensive coordination each same level factor of effect multi-layer appraisement system
Triangular Fuzzy Number carries out significance level judge.
13rd optimal technical scheme provided by the invention, it is improved in that the evaluation computing module includes commenting
Sentence vector location, degree of membership unit and evaluation unit；
The judge vector location is integrated for carrying out fuzzy composition operation using the weight and evaluations matrix
Judge vector；
The degree of membership unit, for obtaining the appraisement system to each evaluation approach according to the Comprehensive Evaluation vector
Degree of membership；
The evaluation unit, for determining evaluation result according to the degree of membership of each evaluation approach.
Compared with the immediate prior art, the device have the advantages that as follows:
The present invention judges knot by the Triangular Fuzzy Number significance level that multiple-energy-source synthesizes and coordinates effect multi-layer appraisement system
Fruit calculates the weight of each factor in the appraisement system, and the marking based on factor in the appraisement system is as a result, obtain evaluations matrix, most
Eventually according to weight and evaluations matrix, the evaluation result of Calculation Estimation system can coordinate and optimize effect from multiple-energy-source, to more
Energy coordination optimization operation is evaluated, and can be used for evaluating energy Internet Engineering.
Detailed description of the invention
Fig. 1 is that a kind of multiple-energy-source provided by the invention synthesizes and coordinates effect evaluation method flow diagram；
Fig. 2 is that a kind of multiple-energy-source provided by the invention synthesizes and coordinates appraisement system schematic diagram in effect evaluation method；
Fig. 3 is that a kind of multiple-energy-source provided by the invention synthesizes and coordinates effect evaluation system basic structure schematic diagram；
Fig. 4 is that a kind of multiple-energy-source provided by the invention synthesizes and coordinates effect evaluation system concrete structure schematic diagram.
Specific embodiment
A specific embodiment of the invention is described in further detail with reference to the accompanying drawing.
Embodiment 1:
A kind of multiple-energy-source comprehensive coordination effect evaluation method flow diagram provided by the invention is as shown in Figure 1, comprising:
Step 1: based between the multiple-energy-source comprehensive coordination each same level factor of effect multi-layer appraisement system pre-established
Triangular Fuzzy Number significance level evaluation result, the weight of each factor in Calculation Estimation system；
Step 2: based on the marking to factor in appraisement system as a result, obtaining evaluations matrix；
Step 3: according to weight and evaluations matrix, the evaluation result of Calculation Estimation system.
Specifically, acquisition multiple-energy-source comprehensive coordination effect evaluation method process includes:
Step 101: establishing assessment indicator system.
Effect is synthesized and coordinated for problem to be evaluated, such as multiple-energy-source, it is comprehensive as multiple-energy-source to establish analytic hierarchy structure
Close trade-off effect multi-layer appraisement system.Remember set of factors U={ U1,U2,…,Un, wherein UiFor i-th in set of factors U because
Element, n are factor of evaluation number, UiIt should meetFor problem to be evaluated, multistage can also be established and commented
Valence system.Subset of factors U by taking two-stage as an example, in UkIn may include Multiple factors, be denoted as Uk={ Uk 1,Uk 2,…,Uk m,
Middle m is subset of factors UkIn factor number.
Step 102: determining each index weights.
The present invention determines the weight of indices using triangle Fuzzy AHP, considers in Judgement Matricies
The ambiguity of expert judgments has been arrived, so that judgment matrix is more reasonable to the characterization of expert opinion, and has avoided consistency check.
Step 102 includes:
Step 102-1: construction fuzzy judgment matrix.
The element a of judgment matrixijExpression is under the jurisdiction of between i-th of factor of lower layer of same upper layer factor and j-th of factor
Relative importance, aijValue (scale) be generally in the range of the natural number and their inverse of 1-9, aij=1/aji, numerical value gets over
Indicate that i-th of factor is more important relative to j-th of factor greatly, as shown in table 1.It is obtained in the present invention using the expert estimation of acquisition
To the judgement information of relative importance, and then form judgment matrix.
1 judgment matrix scale of table and its meaning
Invention applies Triangular Fuzzy Numbers, i.e., the triangle letter determined by three parameters is used in judgment matrix
Number, instead of single numerical value employed in general analytic hierarchy process (AHP), to embody the ambiguity of expert's opinion in multilevel iudge two-by-two.
The subordinating degree function that Triangular Fuzzy Number M is defined is as follows:
In above formula, l, m and u are respectively three parameters of M, l≤m≤u.General Triangular Fuzzy Number M be represented by (l, m,
u)。
Step 102-2: comprehensive significance level is calculated.
Two Triangular Fuzzy Number M1=(l1,m1,u1), M2=(l2,m2,u2) operation method it is as follows:
M1+M2=(l1+l2,m1+m2,u1+u2) (2)
To same group of important ratio compared with the different judges that multidigit expert makes.The judging result for obtaining multiple experts, is answered
With the operational formula of above-mentioned Triangular Fuzzy Number, its arithmetic mean is taken, multiple fuzzy numbers are integrated into one, so that formation one is comprehensive
The fuzzy judgment matrix of conjunction, such as two Triangular Fuzzy Number M1=(l1,m1,u1), M2=(l2,m2,u2) average M0:
Synthesis importance value M of the factor i of kth layer compared with other all factorsi kAs following formula calculates:
Wherein aijFor the Triangular Fuzzy Number that the i-th row jth in fuzzy judgment matrix arranges, indicate i-th of factor relative to same
The importance of j-th of factor of level,WithRespectively aijThree parameters, n be fuzzy judgment matrix ranks
Index number in several namely Indentification model.For the sake of simplicity, it is also possible to DiIndicate i-th of factor with respect to same level other because
The synthesis importance value of element, i.e. formula (6) can turn to:
Step 102-3: de-fuzzy obtains weight vectors.
To two Triangular Fuzzy Number M1=(l1,m1,u1), M2=(l2,m2,u2), M1≥M2Possibility degree be defined as
One fuzzy number MjGreater than same level other n-1 fuzzy number possibility degree namely the fuzzy number is multipair answers index
Weight are as follows:
Wj'=v (Mj≥M1,M2,…,Mn)=min v (Mj≥Mi), i=1,2 ..., n, i ≠ j (8)
It will be via the synthesis significance level M of the counted each factor of formula (6)i kOr DiAs Triangular Fuzzy Number, formula is substituted into
(7), it obtains:
Wherein, DjThe synthesis significance level of expression factor j, DiThe synthesis significance level of expression factor i,WithPoint
It Wei not Triangular Fuzzy Number DjThree parameters,WithRespectively Triangular Fuzzy Number DiThree parameters.
It further substitutes into formula (8), obtains the weight W of each factorj’。
Formula (8) counted weight passes through normalized, can obtain the factor in the final weight of this layer are as follows:
To characterize the weight vectors of each factor weight distribution i.e. are as follows:
W=[w1,w2,…,wn]T (11)
For multiple levels in Indentification model, each Distribution Indexes in specified level can be calculated to obtain by formula (6)-(11)
Weight vectors.
Step 103: establishing evaluate collection.
Evaluation result is divided into λ grade, λ takes odd number, the evaluation that may be made with reflected appraisal person to evaluation object.Note
Evaluate collection is V=[V1,V2,…,Vλ]。
Step 104: Calculation Estimation matrix.
To bottom set of factors UkIn each factor carry out single factor test fuzzy evaluation.It is more based on multiple-energy-source comprehensive coordination effect
Level appraisement system obtains expert to UkEach factor Uk j(j=1,2 ..., m) to the marking result of each evaluation approach；According to beating
Divide as a result, calculating set of factors UkEvaluations matrix Rk.Wherein, m UkMiddle factor number.
Step 105: calculating Comprehensive Evaluation vector.
According to the following Calculation Estimation Comprehensive Evaluation vector of the weight vectors and evaluations matrix that are calculated in preceding step i.e. system
To the degree of membership of each evaluation approach.
Step 105-1: bottom set of factors U is calculatedkCorresponding Comprehensive Evaluation vector.
Bottom set of factors U is calculated firstkEvaluations matrix Rk, and using triangle Fuzzy AHP using formula (6)
~formula (11), can be obtained UkWeight vectors Wk=[wk1,wk2,…,wkm]T, the evaluations matrix that is obtained in conjunction with formula (12)
Rk, make level-one fuzzy comprehensive evoluation, obtain sets of factors UkCorresponding Comprehensive Evaluation vector BkAre as follows:
Wherein,For Fuzzy Arithmetic Operators.
Step 105-2: the corresponding Comprehensive Evaluation vector of other factors collection U other than bottom is calculated.
The corresponding Comprehensive Evaluation vector of multiple lower layer factors collection of acquisition elements collection U first, obtains the evaluations matrix C of U；With
And formula (6)~formula (11) is used using triangle Fuzzy AHP, the corresponding weight matrix W ' of U can be obtained；According to C and
W ' carries out fuzzy comprehensive evoluation, obtains the corresponding Comprehensive Evaluation vector of U.
Wherein, the corresponding Comprehensive Evaluation vector of multiple lower layer factors collection of acquisition elements collection U, obtains the evaluations matrix C of U such as
Following formula:
Wherein, B1..., BnRespectively indicate the corresponding Comprehensive Evaluation vector of lower layer factors collection of U.
According to C and W ', fuzzy comprehensive evoluation is carried out, the corresponding Comprehensive Evaluation vector B ' such as following formula of U is obtained:
Step 105-2 is repeated, simple element evaluation is carried out to other each layer set of factors, finally can be obtained by judge object
Comprehensive Evaluation vector, respectively using each component of Comprehensive Evaluation vector as the degree of membership of the corresponding evaluation approach of the component.
Step 106: obtaining evaluation result.
Evaluation result is determined according to the degree of membership of each evaluation approach.Maximum membership grade principle is used in the present invention, even most
S-th of component of whole Comprehensive Evaluation vector is maximum component, then it represents that multiple-energy-source comprehensive coordination effect belongs to s-th of comment
Grade.
Embodiment 2:
A kind of specific embodiment of multiple-energy-source comprehensive coordination effect evaluation method is given below.
Step 201: Regional Energy internet multiple-energy-source synthesizes and coordinates Effect Evaluation Index System building.
According to the actual conditions of the current energy internet development in China, the present invention is research pair with Regional Energy internet
As studying the mutually coordinated effect between energy internet various energy resources, establishing the comprehensive coordination of Regional Energy internet multiple-energy-source and comment
Valence system, Regional Energy internet multiple-energy-source comprehensive coordination appraisement system of the invention will the comprehensive coordination of source interconnection net multiple-energy-source
It is divided into four aspects: safe operation, coordination optimization, economic benefit and social benefit.
1) it is safely operated
Safe and stable operation is the primary goal in energy internet operational process.Energy internet include it is hot and cold, electric,
A variety of comprehensive energies such as gas, safe and stable operation are the bases for realizing the comprehensive coordination optimization of Regional Energy internet multiple-energy-source.Peace
Row index for the national games is intended to examine in the case of multiple-energy-source coordinated scheduling, the security reliability of operation of power networks in Regional Energy internet.
Common electric power netting safe running index is mainly by supply voltage qualification rate, power supply reliability, three-phase load unbalance degree and electric current
The indexs such as percent harmonic distortion embody.Therefore, one's respective area energy internet security operating index can by supply voltage qualification rate, power supply
It is constituted by four rate, three-phase load unbalance degree and Current harmonic distortion rate indexs.
2) it coordinates and optimizes
In terms of coordination optimization index is intended to examine following four: after various energy resources Optimized Operation, Regional Energy internet
Degree is received to renewable energy；Between hot and cold, electric, gas, between wind energy, luminous energy, water energy and biomass energy etc. various energy resources it
Between mutual benefit and replacement benefit, main mutual benefit and replacement benefit has supply of cooling, heating and electrical powers supersedure effect, substitute gas benefit, biomass
Supersedure effect, earth source heat pump supersedure effect, wind light mutual complementing benefit etc.；It is mutual to Regional Energy after various energy resources coordination optimization operation
The influence of operation of power networks peak-valley difference in networking；Various energy resources are according to respective service capacity characteristic, after coordination optimization scheduling, to line
The influence of the utilization rates of equipment and installations such as road, energy storage.Therefore, coordination optimization index in one's respective area energy internet is mainly connect by renewable energy
Receiving degree, the mutual benefit and replacement benefit of various energy resources, peak-valley difference variation and four indexs of utilization rate of equipment and installations is constituted.
3) economic benefit
Economy be all always related side concern emphasis, energy internet should be able to Optimized Operation and configuration source side and
All kinds of resources of user side, greatly improve the operational efficiency of electric system, reduce the electric cost of user.Economic benefits indicator purport
Generated economic benefit after multiple-energy-source Optimized Operation, is embodied in and reduces electricity power enterprise's equipment in examination Regional Energy net
Investment amount reduces line loss per unit and power grid enterprises' operation maintenance cost, reduces user year loss of outage etc..Therefore, local area
Domain energy internet economy performance indicator mainly reduces percentage by equipment investment, operation maintenance cost reduces percentage, line loss
Rate reduces percentage and Custom interruption cost reduces four indexs of percentage and constitutes.
4) social benefit
Social benefit is intended to examine in Regional Energy net society of institute and environmental benefit, major embodiment after multiple-energy-source Optimized Operation
By using renewable energy, greenhouse gases and toxic gas discharge amount are reduced, reduces temperature by using electric energy alternate device
The discharge of room gas, improve power generation efficiency and reduce energy consumption etc..Thus, energy internet social benefit index in one's respective area is main
It is made of electric energy substitution emission reduction change rate, power generation three indexs of emission reduction change rate and ten thousand yuan of output value energy consumption reduced rates.
According to above-mentioned analysis, Regional Energy internet multiple-energy-source comprehensive coordination effect in China's as shown in Figure 2 can be constructed
Assessment indicator system.The index system contains 4 first class index altogether and 15 two-level index are constituted.
The score basis of each index is as follows.
Appraisement system index scoring of the invention is according to hundred-mark system, using expert graded, by evaluation object be divided into it is high, compared with
It is high, in, lower, low five grades.When the grade of evaluation index score 90~100, evaluation object is height, when evaluation index score
80~90, the grade of evaluation object be it is higher, when evaluation index score 70~80, during the grade of evaluation object is, when evaluation refers to
Mark score 60~70, the grade of evaluation object be it is lower, when evaluation index score at 60 points hereinafter, the grade of evaluation object is
It is low.Expert analysis mode be divided into it is high, higher, in, lower, low five grades, the Primary Reference that expert scores to each index is according to as follows:
(1) supply voltage qualification rate
Supply voltage qualification rate refers in the stipulated time, total time and voltage monitoring of the monitoring point voltage in acceptability limit
The percentage of total time.Its standards of grading: supply voltage qualification rate is greater than 99%, obtains whole standard scores；Supply voltage qualification rate
Between 96% to 99%, 80% standard scores are obtained；Supply voltage qualification rate is less than 96%, not score.
(2) power supply reliability
Power supply reliability=[time during 1- (average power off time of user)/statistics] × 100%.Its standards of grading: it supplies
Electric reliability is greater than 99.99%, obtains whole standard scores；Power supply reliability obtains 80% standard between 99.9% to 99.99%
Point；Power supply reliability is less than 99.9%, not score.
(3) three-phase load unbalance degree
Three-phase load unbalance degree refers to the uneven degree of load three-phase voltage.Its standards of grading: three-phase load is uneven
Weighing apparatus degree obtains whole standard scores less than 1%；Three-phase load unbalance degree obtains 80% standard scores between 1% to 2%；Three-phase load
Degree of unbalancedness is greater than 2%, not score.
(4) Current harmonic distortion rate
Current harmonic distortion rate refers to the ratio between total harmonic current virtual value and fundamental current virtual value.Its standards of grading: electricity
Percent harmonic distortion is flowed less than 5%, obtains whole standard scores；Current harmonic distortion rate obtains 80% standard scores between 5% to 15%；
Supply voltage qualification rate is greater than 15%, not score.
(5) renewable energy acceptance
Renewable energy receives degree mainly to investigate evaluation object to the receiving degree of renewable energy, and mainly including can be again
Raw energy networking power variation rate and access accounting change rate two, respectively account for 50% standard scores.Renewable energy networking power
Change rate=(after coordination optimization before moon networking power-coordination optimization of renewable energy the moon renewable energy networking power)/
The moon networking Power x 100% of renewable energy before coordinating and optimizing, standards of grading: renewable energy networking power variation rate is big
In 30%, whole standard scores are obtained；Renewable energy networking power variation rate obtains 80% standard scores between 10% to 30%；It can
Renewable sources of energy networking power variation rate obtains 60% standard scores between 5% to 10%；Renewable energy networking power variation rate is low
In 5%, not score.Renewable energy access accounting change rate=(coordination optimization year after next renewable energy access accounting-coordination is excellent
Change the year before last renewable energy and access accounting)/coordination optimization the year before last renewable energy access accounting × 100%.Its standards of grading: can
The renewable sources of energy access accounting change rate and are greater than 50%, obtain whole standard scores；Renewable energy access accounting change rate 30% to
Between 50%, 80% standard scores are obtained；Renewable energy accesses accounting change rate between 10% to 30%, obtains 60% standard scores；
Renewable energy accesses accounting change rate and is lower than 10%, not score.
(6) various energy resources mutual benefit and replacement benefit
All kinds of energy have different form and speciality, have complementarity to a certain extent, and multiple-energy-source coordination passes through association
It adjusts using the cold and hot various energy resources such as electrical, realizes making full use of for all kinds of energy, promote the whole efficiency of society to the greatest extent.Gas
The electricity various energy resources Coordination Evaluation standard such as cold and hot: this index mainly investigates the type and load control system ratio of evaluation object using energy source
Example, two respectively account for 50% standard scores.30% standard scores are given when the variety of energy sources that evaluation object is related to reaches 4 kinds, 4 kinds or more are given
Give 50% standard scores.Directly implement the use of the load managements measure such as load control system, interruptible load in load control system ratio=region
Electricity accounts for the ratio of whole electricity consumptions, evaluation criterion: load control system ratio is greater than 50%, obtains whole standard scores；Load control system
Ratio obtains 80% standard scores between 20% to 50%；Load control system ratio is lower than 10%, not score.
(7) peak-valley difference changes
Peak-valley difference variation investigates the maximum peak-valley difference change rate maximum peak-valley difference change rate of evaluation object 10% to 20%
Between, obtain 80% standard scores；Maximum peak-valley difference change rate obtains 60% standard scores between 5% to 10%；Maximum peak-valley difference variation
Rate is lower than 5%, not score.
(8) utilization rate of equipment and installations
Utilization rate of equipment and installations mainly investigates the energy storage device and route utilization power of evaluation object, and two aspects respectively account for 50% mark
Standard point, energy storage match change rate=(energy storage matches after energy storage proportion-coordination optimization before coordinating and optimizing)/proportion before coordinating, energy storage
The renewable energy power generation electricity of energy storage device storing electricity in proportion=moon/in the moon, standards of grading: it is big that energy storage matches change rate
In 30%, whole standard scores are obtained, energy storage matches change rate between 10% to 20%, obtains 80% standard scores, energy storage proportion variation
Rate obtains 60% standard scores between 5% to 10%；Energy storage matches change rate and is lower than 5%, not score；Route daily load change rate
The per day load of=route/route Daily treatment cost × 100%, standards of grading: line load change rate is greater than 10%, obtains entirely
Ministerial standard point；Line load change rate obtains 80% standard scores between 5% to 10%；Line load change rate is lower than 5%, no
Score.
(9) equipment investment reduces percentage
Equipment investment reduces percentage definition: (investment of the equipment such as generating set, energy storage is reduced before multiple-energy-source optimal coordination
The investment amount of generating set, the equipment such as energy storage is reduced after the amount of money-multiple-energy-source optimal coordination) it reduces before/multiple-energy-source optimal coordination
Investment amount × 100% of the equipment such as generating set, energy storage.Its standards of grading: equipment investment reduces percentage and is greater than 10%, obtains
Whole standard scores；Equipment investment reduces percentage between 5% to 10%, obtains 80% standard scores；Equipment investment reduces percentage
Lower than 5%, not score.
(10) operation maintenance cost reduces percentage
Operation maintenance cost reduces percentage definition: (multiple-energy-source optimal coordination the year before last operation expense-multipotency source optimization
Coordinate year after next operation expense) operation expense × 100% before/multiple-energy-source optimal coordination year.Its standards of grading: operation dimension
It protects cost and reduces percentage greater than 10%, obtain whole standard scores；Operation maintenance cost reduces percentage between 5% to 10%,
Obtain 80% standard scores；Operation maintenance cost reduces percentage and is lower than 5%, not score.
(11) line loss per unit reduces percentage
Line loss per unit reduces percentage and defines: (line loss per unit after line loss per unit-multiple-energy-source optimal coordination before multiple-energy-source optimal coordination)/
Line loss per unit × 100% before multiple-energy-source optimal coordination, standards of grading: line loss per unit reduces percentage and is greater than 20%, obtains whole standards
Point；Line loss per unit reduces percentage between 10% to 20%, obtains 80% standard scores；Line loss per unit reduces percentage and is lower than 10%, no
Score.
(12) Custom interruption cost reduces percentage
User year loss of outage reduces percentage definition: (user year loss of outage-multiple-energy-source is excellent before multiple-energy-source optimal coordination
Change user's year loss of outage after coordinating) user year loss of outage × 100% before/multiple-energy-source optimal coordination.Its standards of grading: user
Year loss of outage reduction percentage is greater than 10%, obtains whole standard scores；User year loss of outage reduces percentage 5% to 10%
Between, obtain 80% standard scores；User year loss of outage reduces percentage and is lower than 5%, not score.
(13) electric energy substitutes emission reduction change rate
Electric energy substitutes the definition of emission reduction change rate: (using electric energy alternate device institutes such as electric heating, electric boilers after coordination optimization
Before CO2 emissions-coordination optimization of reduction using the electric energy alternate device such as electric heating, electric boiler reduction titanium dioxide
Carbon emission amount) after/coordination optimization using the electric energy alternate device such as electric heating, electric boiler reduction CO2 emissions ×
100%, the electric energy alternate device such as electric heating, electric boiler caused by CO2 emissions=original coal combustion equipment of reduction
CO2 emissions (kg) caused by CO2 emissions+original oil burning boiler=original coal combustion equipment year consumption combustion
The original fuel oil equipment year fuel consumption total amount (L) × 2.63 of coal total amount (kg) × 2.49+, standards of grading: electric energy substitutes emission reduction
Quantitative change rate is greater than 10%, obtains whole standard scores；Electric energy substitutes emission reduction change rate between 5% to 10%, obtains 80% standard
Point；Electric energy substitutes emission reduction change rate and is lower than 5%, not score.
(14) generate electricity emission reduction change rate
Generate electricity the definition of emission reduction change rate: (renewable energy annual electricity generating capacity is converted into same thermal power generation after coordination optimization
After unit generation amount, renewable energy annual electricity generating capacity is converted into same fire before generated CO2 emissions-coordination optimization
After power generator group generated energy, generated CO2 emissions)/coordinate and optimize before renewable energy annual electricity generating capacity be converted into
After same thermal power generation unit generated energy, generated CO2 emissions × 100%, same thermal power generation carbon dioxide row
High-volume (kg)=thermal power generation total amount (kWh) × 0.78, standards of grading: renewable energy power generation emission reduction change rate is greater than
10%, obtain whole standard scores；Renewable energy power generation emission reduction change rate obtains 80% standard scores between 5% to 10%；It can be again
Raw energy power generation emission reduction change rate is lower than 5%, not score.
(15) ten thousand yuan of output value energy consumption reduced rates
Ten thousand yuan of output value energy consumption reduced rate definition: ten thousand yuan of output value energy consumption reduced rates=(coordination optimization preceding ten thousand yuan of output value energy inputs-
Ten thousand yuan of output value energy inputs after coordination optimization)/preceding ten thousand yuan of output value energy input × 100%, ten thousand yuan output value energy input (t/ ten thousand of coordination optimization
Member)=year total electricity consumption amount (kWh)/(6944.4 × year region gross output value), standards of grading: ten thousand yuan of output value energy consumption reduced rates are big
In 5%, whole standard scores are obtained；Ten thousand yuan of output value energy consumption reduced rates obtain 80% standard scores between 1% to 5%；Ten thousand yuan of output value energy consumptions
Reduced rate is lower than 1%, not score.
Step 202: calculating weight, comprising:
Step 202-1: construction fuzzy judgment matrix.
Construct triangle fuzzy judgment matrix A=(aij)n×n, the wherein element of matrixExpression is commented
Importance value of i-th of factor with respect to j-th of factor of same level in valence system；It is exactly two in usual step analysis
Two used scale numbers when comparing, the scale used here is as shown in table 1, and the Triangle Module of three parameters is used in the present invention
Paste number As scale number used when comparing two-by-two.In addition,Wherein, t=1,2 ..., T, aij tThe triangle ambiguity function provided for t-th of expert.
Step 202-2: comprehensive importance value is calculated
Synthesis importance value M of each factor of kth layer compared with other all factorsi k, and
Step 202-3: weight vectors are calculated.
Step 202-3 is specifically included:
Calculate a fuzzy number MjGreater than same level other n-1 fuzzy number possibility degree namely the fuzzy number is multipair answers
Index weights are as follows:
Wj'=v (Mj≥M1,M2,…,Mn)=min v (Mj≥Mi), i=1,2 ..., n, i ≠ j (8)
It will be substituted into formula (8) via the value of the synthesis significance level of the counted each factor of formula (6) as Triangular Fuzzy Number
Obtain the weight W of each factorj’。
Wj' pass through normalized, can obtain the index in the final weight of this layer is
It is to characterize the weight vectors of each factor weight distribution
W=[w1,w2,…,wn]T (11)
Step is determined according to weight described above, and effect is synthesized and coordinated according to the Regional Energy internet multiple-energy-source of building
Assessment indicator system respectively asks an expert from power supply company, colleges and universities and electric power research unit, to 4 factors of first layer by important
Degree is compared two-by-two, obtains fuzzy judgment matrix such as the following table 2 of level A-B.
The fuzzy judgment matrix that 2 three experts of table provide
Arithmetic mean is taken to the Triangular Fuzzy Number for the fuzzy judgment matrix that three experts provide, obtains level A-B's
Fuzzy judgment matrix.
The fuzzy judgment matrix of 3 A-B of table
Similarly, the available B-C fuzzy judgment matrix taken after arithmetic mean:
4 B1-C fuzzy judgment matrix of table
5 B2-C fuzzy judgment matrix of table
6 B3-C fuzzy judgment matrix of table
7 B4-C fuzzy judgment matrix of table
It to each fuzzy judgment matrix, can be calculated using formula (6)~(11), the weight vector of each judgment matrix such as following table.
The weight vectors of 8 judgment matrix of table
Here shown in the table 3 for A-B fuzzy judgment matrix, the step of determining weight vectors is further described:
According to the data in table 3,
Similarly:It is calculated according to formula (6):
Again to DB1, DB2, DB3, DB4De-fuzzy:
V(DB1≥DB3)=1；V(DB1≥DB4)=1；V(DB2≥DB1)=1
V(DB2≥DB3)=1；V(DB2≥DB4)=1
V(DB3≥DB1)=0.9583；V(DB3≥DB2)=0.8622；V(DB3≥DB4)=1；
V(DB4≥DB1)=0.2247；V(DB4≥DB2)=0.1349；V(DB4≥DB3)=0.2872
w1'=minV (D1≥D2,D3,D4)=minV (D1≥Di)=min (0.8913,1,1)=0.8913
w2'=min V (D2≥D1,D3,D4)=minV (D1≥Di)=min (1,1,1)=1
w3'=min V (D3≥D1,D2,D4)=minV (D1≥Di)=min (0.9583,0.8622,1)=0.8622
w4'=min V (D4≥D1,D2,D3)=minV (D1≥Di)=min (0.2247,0.1349,0.2872)=
0.1349
It is obtained after normalization:
(w1,w2,w3,w4)T=(0.3086,0.3462,0.2985,0.0467)T
Obtain A-B weight vector shown in table 8.
Step 203 determines evaluation object equivalence according to maximum membership grade principle
By taking certain northern Regional Energy internet demonstration project as an example, evaluated according to triangle Fuzzy AHP.
Remember that multiple-energy-source synthesizes and coordinates level set V=[V1,V2,V3,V4,V5]T=[it is high, it is higher, in, it is lower, low] T.Selection
10 industry specialists (Utilities Electric Co. 4,3, colleges and universities, scientific research institution 3) constitute evaluation group, provide the demonstration work for expert
Cheng Xiangguan particulars ask expert estimation with each single factor evaluation matrix of determination.Expert estimation result such as table 9:
9 expert estimation result of table
Obtain single factor evaluation matrix RiIt only needs that number value of giving a mark in marking table is simply converted to marking ratio i.e.
Can, such as 3 experts of the first row think to power that qualification rate is high, and 4 are thought higher, and in 2,1 is lower；Then RiThe first row is
(0.3,0.4,0.2,0.1,0).
Evaluations matrix is obtained according to expert estimation table, wherein the evaluation of the B1-C of table 4 can must be corresponded to by 1~4 row in table 9
Matrix R1, the evaluations matrix R of the B2-C of table 5 can must be corresponded to by 5~8 rows in table 92, table 6 can must be corresponded to by 9~12 rows in table 9
The evaluations matrix R of B3-C3, the evaluations matrix R of the B4-C of table 7 can must be corresponded to by 13~15 rows in table 94。
It can be obtained by table 8, the weight vectors W of the B1-C of corresponding table 41For (0.43,0.45,0.03,0.10)T, corresponding table 5
The weight vectors W of B2-C2For (0.34,0.54,0.06,0.06)T, the weight vectors W of the B3-C of corresponding table 63For (0.50,
0.04,0.27,0.19)T, the weight vectors W of the B4-C of corresponding table 74For (0.48,0.41,0.11)T。
Total evaluations matrix can be calculated by formula (14) are as follows:
B '=W ' DEG C is obtained as Secondary Fuzzy Comprehensive Evaluation, wherein W ' is using the A-B weight vectors in table 8, B '=W ' DEG C=
(0.31,0.38,0.24,0.09,0.00)T.It obtains according to maximum membership grade principle, the multiple-energy-source of the Regional Energy internet is comprehensive
It is preferable to close trade-off effect.
Wherein, it is B=(b that maximum membership grade principle, which refers to the assumption that Comprehensive Evaluation vector,1,b2,…,bn), B=W ° of R, if bs
=maxB is then evaluated object and is generally speaking just under the jurisdiction of s grade, and here it is maximum membership grade principles.For example, if synthesis is commented
Valence vector B=(0.563,0.362,0.070,0.003,0.002)T, it is 0.563 because of the 1st component maximum in vector, in
It is that then can be determined that evaluation object is under the jurisdiction of the 1st evaluation approach according to maximum membership grade principle
Embodiment 3:
Based on the same inventive concept, the present invention also provides a kind of multiple-energy-sources to synthesize and coordinate effect evaluation system, due to this
The principle that a little equipment solve technical problem is similar to multiple-energy-source comprehensive coordination effect evaluation method, and overlaps will not be repeated.
The system basic structure is as shown in Figure 3, comprising: weight module, evaluations matrix module and evaluation computing module；
Wherein, weight module, for each same based on the multiple-energy-source comprehensive coordination effect multi-layer appraisement system pre-established
Triangular Fuzzy Number significance level evaluation result between level factor, the weight of each factor in Calculation Estimation system；
Evaluations matrix module, for based on the marking to factor in appraisement system as a result, obtaining evaluations matrix；
Computing module is evaluated, for according to weight and evaluations matrix, the evaluation result of Calculation Estimation system.
The system specific structure is as shown in Figure 4.
Wherein, weight module includes comprehensive significance level unit and weight unit；
Comprehensive significance level unit, for being based on significance level evaluation result, each factor is relatively same in Calculation Estimation system
The synthesis significance level of one level other factors；
Weight unit, for according to comprehensive significance level, the weight of each level factor in Calculation Estimation system；
Wherein, the triangle of three parameters is used between multiple-energy-source comprehensive coordination each same level factor of effect multi-layer appraisement system
Fuzzy number carries out significance level judge.
Wherein, it is based on significance level evaluation result, each factor is with respect to same level other factors in Calculation Estimation system
Comprehensive significance level, is shown below:
Wherein, DiFor factor i with respect to same level other factors synthesis importance value, n be factor i where level because
The total number of element, aijTriangular Fuzzy Number significance level evaluation result between expression factor i and same level factor j,WithRespectively Triangular Fuzzy Number aijThree parameters.
Wherein, according to significance level is integrated, the weight of each level factor in Calculation Estimation system is shown below:
Wj'=v (Dj≥D1,D2,…,Dn)=min v (Dj≥Di), i=1,2 ..., n, i ≠ j
Wherein, wjThe weight of j-th of factor of ' expression, DjThe synthesis significance level of expression factor j, DiExpression factor i's is comprehensive
Close significance level, v (Dj≥D1,D2,…,Dn) indicate DjMore than or equal to the possibility of the comprehensive significance level of same level other factors
Degree, v (Dj≥Di) indicate Dj≥DiPossibility degree, v (Dj≥Di) such as following formula calculating:
Wherein,WithRespectively Triangular Fuzzy Number DjThree parameters,WithRespectively triangle is fuzzy
Number DiThree parameters.
Wherein, give a mark to factor in appraisement system, including to factor in appraisement system to the degree of membership of each evaluation approach into
Row marking.
Wherein, evaluation computing module includes judging vector location, degree of membership unit and evaluation unit；
Vector location is judged, for carrying out fuzzy composition operation using weight and evaluations matrix, obtains Comprehensive Evaluation vector；
Degree of membership unit, for obtaining appraisement system to the degree of membership of each evaluation approach according to Comprehensive Evaluation vector；
Evaluation unit, for determining evaluation result according to the degree of membership of each evaluation approach.
Wherein, judging vector location includes bottom subelement and upper subelement；
Bottom subelement is obtained for carrying out fuzzy composition operation using the corresponding evaluations matrix of bottom set of factors and weight
To the corresponding Comprehensive Evaluation vector of bottom set of factors；
Upper subelement, for acquire the corresponding Comprehensive Evaluation of lower layer factors collection of the non-bottom set of factors evaluated to
Amount, obtains the corresponding evaluations matrix of non-bottom set of factors evaluated, using the corresponding evaluations matrix of progress factor of evaluation collection
Fuzzy composition operation is carried out with weight, obtains the corresponding Comprehensive Evaluation vector of non-bottom set of factors evaluated.
Wherein, bottom subelement calculates the corresponding Comprehensive Evaluation vector of bottom set of factors using following formula:
Wherein, B indicates that the corresponding Comprehensive Evaluation vector of appraisement system bottom factor, W indicate the corresponding power of bottom set of factors
Weight, R indicate the corresponding evaluations matrix of bottom factor,Indicate Fuzzy Arithmetic Operators.
Wherein, upper subelement acquisition carries out the corresponding Comprehensive Evaluation vector of lower layer factors collection of factor of evaluation collection, obtains
The corresponding evaluations matrix of factor of evaluation collection is carried out, is shown below:
Wherein, C indicates the corresponding evaluations matrix of carry out factor of evaluation collection other than bottom, B1..., BnRespectively indicate progress
The corresponding Comprehensive Evaluation vector of each lower layer factors collection of factor of evaluation collection.
Wherein, upper subelement carries out fuzzy composition fortune using the corresponding evaluations matrix of progress factor of evaluation collection and weight
It calculates, obtains progress factor of evaluation collection and correspond to Comprehensive Evaluation vector, be shown below:
Wherein, B ' indicates that the corresponding Comprehensive Evaluation vector of carry out factor of evaluation collection other than bottom, W ' indicate other than bottom
The corresponding weight of carry out factor of evaluation collection,Indicate Fuzzy Arithmetic Operators.
Wherein, degree of membership unit is respectively using each component of Comprehensive Evaluation vector as the person in servitude of the corresponding evaluation approach of the component
Category degree.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Finally it should be noted that: above embodiments are merely to illustrate the technical solution of the application rather than to its protection scopes
Limitation, although the application is described in detail referring to above-described embodiment, those of ordinary skill in the art should
Understand: those skilled in the art read the specific embodiment of application can still be carried out after the application various changes, modification or
Person's equivalent replacement, but these changes, modification or equivalent replacement, are applying within pending claims.
Claims (15)
1. a kind of multiple-energy-source synthesizes and coordinates effect evaluation method, it is characterised in that:
The Triangular Fuzzy Number between each same level factor of effect multi-layer appraisement system is synthesized and coordinated based on the multiple-energy-source pre-established
Significance level evaluation result calculates the weight of each factor in the appraisement system；
Based on the marking to factor in the appraisement system as a result, obtaining evaluations matrix；
According to the weight and the evaluations matrix, the evaluation result of the appraisement system is calculated.
2. the method as described in claim 1, which is characterized in that described more based on the multiple-energy-source pre-established comprehensive coordination effect
Triangular Fuzzy Number significance level evaluation result between each same level factor of level appraisement system, calculate in the appraisement system it is each because
The weight of element, comprising:
It is fuzzy using the triangle of three parameters between multiple-energy-source comprehensive coordination each same level factor of effect multi-layer appraisement system
Number carries out significance level judge；
Based on the significance level evaluation result, it is comprehensive with respect to same level other factors to calculate each factor in the appraisement system
Close significance level；
According to the comprehensive significance level, the weight of each level factor in the appraisement system is calculated.
3. method according to claim 2, which is characterized in that it is described to be based on the significance level evaluation result, described in calculating
Each factor is shown below with respect to the synthesis significance level of same level other factors in appraisement system:
Wherein, DiSynthesis importance value for factor i with respect to same level other factors, n are level factor where factor i
Total number, aijTriangular Fuzzy Number significance level evaluation result between expression factor i and same level factor j,WithRespectively Triangular Fuzzy Number aijThree parameters.
4. method as claimed in claim 3, which is characterized in that it is described according to the comprehensive significance level, calculate the evaluation
The weight of each level factor in system, is shown below:
Wj'=v (Dj≥D1,D2,…,Dn)=min v (Dj≥Di), i=1,2 ..., n, i ≠ j
Wherein, wjThe weight of j-th of factor of ' expression, DjThe synthesis significance level of expression factor j, DiThe comprehensive weight of expression factor i
Want degree, v (Dj≥D1,D2,…,Dn) indicate DjMore than or equal to the possibility degree of the comprehensive significance level of same level other factors, v
(Dj≥Di) indicate Dj≥DiPossibility degree, v (Dj≥Di) such as following formula calculating:
Wherein,WithRespectively Triangular Fuzzy Number DjThree parameters,WithRespectively Triangular Fuzzy Number Di
Three parameters.
5. the method as described in claim 1, which is characterized in that give a mark to factor in the appraisement system, including to institute's commentary
Factor gives a mark to the degree of membership of each evaluation approach in valence system.
6. method as claimed in claim 5, which is characterized in that it is described according to the weight and the evaluations matrix, calculate institute
State the evaluation result of appraisement system, comprising:
Fuzzy composition operation is carried out using the weight and evaluations matrix, obtains Comprehensive Evaluation vector；
According to the Comprehensive Evaluation vector, the appraisement system is obtained to the degree of membership of each evaluation approach；
Evaluation result is determined according to the degree of membership of each evaluation approach.
7. method as claimed in claim 6, which is characterized in that described to be obscured using the evaluations matrix and weight matrix
Operation is synthesized, Comprehensive Evaluation vector is obtained, comprising:
If carrying out the evaluation of bottom set of factors, fuzzy composition fortune is carried out using the corresponding evaluations matrix of bottom set of factors and weight
It calculates, obtains the corresponding Comprehensive Evaluation vector of bottom set of factors；
Otherwise, acquisition carries out the corresponding Comprehensive Evaluation vector of lower layer factors collection of factor of evaluation collection, obtains carrying out factor of evaluation collection
Corresponding evaluations matrix carries out fuzzy composition operation using the corresponding evaluations matrix of the progress factor of evaluation collection and weight, obtains
To the corresponding Comprehensive Evaluation vector of progress factor of evaluation collection.
8. the method for claim 7, which is characterized in that described using the corresponding evaluations matrix of bottom set of factors and weight
Fuzzy composition operation is carried out, the corresponding Comprehensive Evaluation vector of bottom set of factors is obtained, is shown below:
Wherein, B indicates that the corresponding Comprehensive Evaluation vector of the appraisement system bottom factor, W indicate the corresponding power of bottom set of factors
Weight, R indicate the corresponding evaluations matrix of bottom factor,Indicate Fuzzy Arithmetic Operators.
9. the method for claim 7, which is characterized in that the lower layer factors collection that the acquisition carries out factor of evaluation collection is corresponding
Comprehensive Evaluation vector, obtain carrying out the corresponding evaluations matrix of factor of evaluation collection, be shown below:
Wherein, C indicates the corresponding evaluations matrix of carry out factor of evaluation collection other than bottom, B1..., BnIt respectively indicates and is evaluated
The corresponding Comprehensive Evaluation vector of each lower layer factors collection of set of factors.
10. method as claimed in claim 9, which is characterized in that described to use the corresponding evaluation of the progress factor of evaluation collection
Matrix and weight carry out fuzzy composition operation, obtain progress factor of evaluation collection and correspond to Comprehensive Evaluation vector, are shown below:
Wherein, B ' indicates that the corresponding Comprehensive Evaluation vector of the carry out factor of evaluation collection other than bottom, W ' indicate other than bottom
The corresponding weight of the carry out factor of evaluation collection,Indicate Fuzzy Arithmetic Operators.
11. method as claimed in claim 6, which is characterized in that it is described according to the Comprehensive Evaluation vector, obtain the evaluation
Degree of membership of the system to each evaluation approach, comprising:
Respectively using each component of the Comprehensive Evaluation vector as the degree of membership of the corresponding evaluation approach of the component.
12. the method as described in claim 1, which is characterized in that the multiple-energy-source synthesizes and coordinates effect multi-layer appraisement system
Factor of evaluation include:
Safe operation, coordination optimization, economic benefit and social benefit；
The safe operation includes: that supply voltage qualification rate, power supply reliability, three-phase load unbalance degree and current harmonics are abnormal
Variability；
The coordination optimization includes: renewable energy acceptance, various energy resources mutual benefit and replacement benefit, peak-valley difference variation and equipment benefit
With rate；
The economic benefit includes: that equipment investment reduces percentage, operation maintenance cost reduces percentage, line loss per unit reduces percentage
Than reducing percentage with Custom interruption cost；
The social benefit includes: that electric energy substitution emission reduction change rate, power generation emission reduction change rate and ten thousand yuan of output value energy consumptions change
Rate.
13. a kind of multiple-energy-source synthesizes and coordinates effect evaluation system, which is characterized in that including weight module, evaluations matrix module and
Evaluate computing module；
The weight module, for based on pre-establish multiple-energy-source comprehensive coordination each same level of effect multi-layer appraisement system because
Triangular Fuzzy Number significance level evaluation result between element, calculates the weight of each factor in the appraisement system；
The evaluations matrix module, for based on the marking to factor in the appraisement system as a result, obtaining evaluations matrix；
The evaluation computing module, for calculating the evaluation knot of the appraisement system according to the weight and the evaluations matrix
Fruit.
14. system as claimed in claim 13, which is characterized in that the weight module include: comprehensive significance level unit and
Weight unit；
The comprehensive significance level unit, for be based on the significance level evaluation result, calculate in the appraisement system it is each because
The synthesis significance level of the opposite same level other factors of element；
The weight unit, for calculating the weight of each level factor in the appraisement system according to the comprehensive significance level；
Wherein, the triangle of three parameters is used between multiple-energy-source comprehensive coordination each same level factor of effect multi-layer appraisement system
Fuzzy number carries out significance level judge.
15. system as claimed in claim 13, which is characterized in that the evaluation computing module includes judging vector location, being subordinate to
Category degree unit and evaluation unit；
The judge vector location obtains Comprehensive Evaluation for carrying out fuzzy composition operation using the weight and evaluations matrix
Vector；
The degree of membership unit, for obtaining the appraisement system to the person in servitude of each evaluation approach according to the Comprehensive Evaluation vector
Category degree；
The evaluation unit, for determining evaluation result according to the degree of membership of each evaluation approach.
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