CN106952015A - A kind of method for improving charging electric vehicle facilities planning quality - Google Patents

Abstract

A kind of method for improving charging electric vehicle facilities planning quality.It includes the classification indicators for determining to there is influence to the scheme of raising charging electric vehicle facilities planning quality to be assessed first；Construct fuzzy judgment matrix：Calculate obfuscation weight；De-fuzzy；Set up evaluate collection；The steps such as multi-layer fuzzy comprehensive.The beneficial effect of the method for the raising charging electric vehicle facilities planning quality that the present invention is provided：Using analytic hierarchy process (AHP), the influence of multiple factors is considered with reference to actual conditions, with very high theory value and actual effect；Overall merit is carried out to programme using fuzzy synthetic appraisement method, optimal programme is determined.

Description

A kind of method for improving charging electric vehicle facilities planning quality

Technical field

The invention belongs to the planning technology field of charging electric vehicle facility, more particularly to a kind of electric automobile that improves fills The method of electric facilities planning quality.

Background technology

Energy shortage has become the problem of whole world is paid close attention to the most with environmental degradation, and energy-saving and emission-reduction are that China's economy is persistently sent out The problem of opening up in the urgent need to address.Electric automobile has the features such as replacing oil by electricity, tail gas " zero-emission ", is to solve the energy and environment The important means of problem.Large-scale electric automobile is also used as distributed energy storage device, can be used by power system.In recent years Come, State Council, the Party Central Committee promote to new-energy automobile and charging infrastructure construction aspect imparts unprecedented attention With enthusiasm, deploy quickening charging electric vehicle infrastructure and urban parking area construction, mend in the promotion expansion of public service short slab The motion for needing Huimin to give birth to；Clearly proposed first in the government work report in 2015 and formulated " internet+" action plan, it is intended to Promotion Internet technology is merged with modern manufacturing industry, and new opportunity is provided for charging electric vehicle infrastructure construction, is pushed away Motor-car networked platforms are built.

The end of the year 2015 had been achieved with car networking platform on-line running in cities such as Beijing, Tianjin.On the one hand it is electrically-charging equipment Operation provides the complete service functions such as facility access, operation monitoring, charging reservation and disbursement and sattlement, on the other hand will be electronic vapour Bring internet+charging service experience in automobile-used family.Platform is used as main interaction using easy charging service website and e charge mobile phones APP Means, electrically-charging equipment position and status inquiry, automobile navigation, unified recharged card Zhi Fuyu are provided without card branch for automobile user Pay and wait charging service, while supporting government to realize charging service supervision and electrically-charging equipment programming and distribution, support charging service Industry development, realizes resource consolidation, interconnects.Realization is closed by the O2O of " charging equipment under APP+ charging networks+line on line " People, car, stake are together in series by ring, so as to obtain realization profitable offering.

But at present, due to new-energy automobile electrically-charging equipment imperfection, it is difficult to which meeting existing new-energy automobile charging continuation of the journey will Ask, it has also become current and future promotes the major obstacle of new-energy automobile, it is necessary to increase publicity promotion efficiency in one period, and Make Revenue Sharing Mechanism in order, improve understanding and acceptance level of the related site manager to charging pile, while innovation charging modes, Reduce land used difficulty etc. and build resistance, place problem is built in neutralizing, accelerate popularization and lay charging pile.

The related auxiliary facility of the development need of electric automobile.Electrically-charging equipment is to electric motor car just as gas station is to orthodox car one Sample, is indispensable infrastructure.But the construction of charging equipment at this stage needs huge investment and systems organization, and need Rely on fund, policy of government etc. to help, electric automobile is because of auxiliary facility imperfection slower development, and auxiliary facility is because of electronic vapour Car popularity rate is low to lack popularization power.The relevant benefit main body that Development of Electric Vehicles is related to is more, there is power supply enterprise, operation enterprise Industry, supporting enterprise, vehicle enterprise, battery enterprise etc..Lack in huge interest group and be uniformly coordinated mechanism, Interest Main Body phase Lack between mutually and make a concerted effort, electric vehicle industrialization process can be directly influenced.Charging electric vehicle facility is ev industry The premise and important foundation of popularization, are also electric automobile commercialization, the important step of industrialization.International Meteorological Organization is to 40 multidigits The interview result of electric automobile relevant industries expert shows that the significance level that electrically-charging equipment is built is in the numerous shadows of Development of Electric Vehicles Battery technology is only second in the factor of sound to be number two, basic, the key effect each side of electrically-charging equipment has reached common understanding.Institute When carrying out charging electric vehicle facilities planning, to fully take into account developing stage, the use demand of user of electric automobile Deng, it is ensured that fund improves the convenient and swift of charging with the maximum service ability of electrically-charging equipment on blade, is played, and helps to carry High electric automobile is popularized.

In current charging electric vehicle facilities planning scheme, the quantity of all types of electric automobiles is mainly estimated, The demand of charging times and charge volume is calculated with reference to VMT Vehicle-Miles of Travel etc., the service ability of combined charge stake is calculated and filled The total number of electric stake.But have the disadvantage not consider to build the factor such as place and fund input, policy is stronger, and practicality is not high.

The content of the invention

In order to solve the above problems, charging electric vehicle facilities planning quality is improved it is an object of the invention to provide one kind Method.

In order to achieve the above object, the method for the raising charging electric vehicle facilities planning quality that the present invention is provided includes pressing The following steps that order is performed：

Step 1) determine there is influence to the scheme of raising charging electric vehicle facilities planning quality to be assessed first Classification indicators, referred to as the first level factor, by these index composing indexes classification layer, every class index is subdivided into certain general character Multiple the second level factors, these the second level factor composing indexes layers；It is denoted as set of factors U={ U₁,U₂,…,U_n, wherein U_iFor set of factors U In i-th of factor, U_iIt should meet

Step 2) construction fuzzy judgment matrix：The element c of judgment matrix_ijRepresent to be under the jurisdiction of the lower floor the of same upper strata element Relative importance between i element and j-th of element, c_ijValue (scale) scope for 1-9 natural number and they fall Number, c_ij=1/c_ji, numerical value is bigger to represent that relative to j-th element of i-th of element is more important, as shown in table 1；

The judgment matrix scale of table 1 and its implication

Triangle Fuzzy Evaluation Method applies Triangular Fuzzy Number, i.e., one determined by three numerals is used in judgment matrix Triangular function, instead of single numerical value employed in general evaluation method, to embody the mould of expert's opinion in multilevel iudge two-by-two Paste property；

Step 3) calculate obfuscation weight：To same group of important ratio compared with the different judges that multidigit expert makes, application The operational formula of Triangular Fuzzy Number is to two Triangular Fuzzy Number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂) computing, take it to count It is average, multiple fuzzy numbers are integrated into one, so as to form the fuzzy judgment matrix of a synthesis；

Step 4) de-fuzzy：For two fuzzy number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂), M₁≥M₂Possibility Degree, calculates a fuzzy number M_jMore than this layer other n-1 fuzzy number possibility degree namely the fuzzy number more than correspondence index power Weight, by normalized, can obtain final weight of the index in this layer, so as to characterize the power of this layer of each index weights distribution Weight vector；

Step 5) set up evaluate collection：Evaluation result is divided into λ grade, λ takes odd number, with reflected appraisal person to evaluation object The evaluation that may be made；Note evaluate collection is V=[V₁,V₂,…,V_λ]^T；

Step 6) multi-layer fuzzy comprehensive：To bottom set of factors U_i(i=1,2 ..., n) in each factor carry out Single factor test fuzzy evaluation, according to expert estimation, obtains factor U_ij(j=1,2 ..., m) to the degree of membership of each grade comment, so that It can obtain set of factors U_iSingle factor test fuzzy judgment matrix；

Using triangle Fuzzy Evaluation Method, set of factors U can obtain_iWeight vectors W_i=[w_i1,w_i2,…,w_in]^T, make one-level Fuzzy comprehensive evoluation, obtains factor U_iTo the degree of membership of each grade comment；

Ibid, simple element evaluation is carried out to other each layer set of factors, finally can obtain by judge object to each grade comment Degree of membership, so as to evaluation result.

In step 2) in, the membership function that described Triangular Fuzzy Number M is defined is as follows：

In above formula, l≤m≤u, l and u represent lower bound and the upper bound of the Triangular Fuzzy Number, and m represents the intermediate value that degree of membership is 1； General Triangular Fuzzy Number M is represented by (l, m, u).

In step 3) in, two described three fuzzy number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂) operation method such as Under：

M₁+M₂=(l₁+l₂,m₁+m₂,u₁+u₂) (2)

To same group of important ratio compared with the different judges that multidigit expert makes, using the computing of above-mentioned Triangular Fuzzy Number Formula, takes its arithmetic mean, and multiple fuzzy numbers are integrated into one, so as to form the fuzzy judgment matrix of a synthesis；

To kth layer element i fuzzy weighted values Di, computing formula is as follows

Wherein a_ijThe Triangular Fuzzy Number arranged for the i-th row jth in fuzzy judgment matrix, represents i-th of element relative to j-th The importance of element.

In step 4) in, it is described to two fuzzy number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂), M₁≥M₂Possibility Degree is defined as：

One fuzzy number M_jMore than this layer other n-1 fuzzy number possibility degree namely the fuzzy number more than correspondence index power Weight is：

w_cj'=ν (M >=M₁,M₂,…,M_n)=min ν (M >=M_i), i=1,2 ..., n (7)

By normalized, the final weight that can obtain the index in this layer is

So as to which the weight vectors for characterizing this layer of each index weights distribution are

W_i=[w₁,w₂,…,w_n]^T (9)。

In step 6) in, described set of factors U_iSingle factor test fuzzy judgment matrix be：

Described factor U_iDegree of membership to each grade comment is

In formulaFor Fuzzy Arithmetic Operators.

The beneficial effect of the method for the raising charging electric vehicle facilities planning quality that the present invention is provided：The present invention uses layer Fractional analysis, the influence of multiple factors is considered with reference to actual conditions, with very high theory value and actual effect；Using mould Paste integrated evaluating method and overall merit is carried out to programme, determine optimal programme.

Brief description of the drawings

Fig. 1 is the decomposition chart that electrically-charging equipment of the present invention is planned.

The electrically-charging equipment planning index system figure that Fig. 2 provides for the present invention.

Embodiment

The raising charging electric vehicle facilities planning quality provided below in conjunction with the accompanying drawings with specific embodiment the present invention Method is described in detail.

Charging electric vehicle facilities planning is a complication system, and its influence factor is numerous, mainly there is the class of electric automobile Type, use habit, charging modes, the target expectation using electric automobile, car owner not only wrap to level of application of internet etc. Include qualitative index, and including quantitative target, only with simple method, be difficult often evaluate between each factor, each level Between quality.Therefore, the planning and evaluation of carry out scheme are combined using analytic hierarchy process (AHP) and Field Using Fuzzy Comprehensive Assessment.

The index of charging electric vehicle facilities planning is classified, classified, recursive hierarchy structure index system is built such as Shown in Fig. 1, in classification, the index system of taxonomic structure, there are several indexs per class, similar index has certain general character, Inhomogeneous index is differed to the influence produced by general objective, thus can not be put on an equal footing.Add between target and indicator layer Enter an index classification layer, make the hierarchical structure of index system clearer, be more beneficial for the analysis to problem.Fig. 2 is this hair Bright electrically-charging equipment planning index system, including electrically-charging equipment demand, technology development, build the input of place and fund.

SG-MCA (intelligent grid-multi-standard analysis) is the intelligent grid of a kind of combination SG-MCA evaluation assessments and fuzzy logic The Benefit Evaluation Method of project.Multiobjective decision-making is a branch of operational research, is a famous decision domain.This method It is contemplated that great society, economy and ambient influnence, it is particularly possible to embody the demand of multi-party participant in decision process.

SG-MCA general principle is that the various key elements of the relevant scheme of evaluation system are resolved into some levels, forms one The individual orderly hierarchy Model for passing rank, and a level key element is carried out two-by-two thereon relatively by each key element of each level Multilevel iudge, obtains the weight of each key element.Weight limit principle optimum scheme comparison is pressed according to comprehensive weight.

The method take into account the ambiguity of expert judgments in Judgement Matricies so that judgment matrix is to expert opinion Sign it is more reasonable, and avoid consistency check.

As shown in Fig. 1-Fig. 2, the method for the raising charging electric vehicle facilities planning quality that the present invention is provided is included by suitable The following steps that sequence is performed：

Step 1) determine there is influence to the scheme of raising charging electric vehicle facilities planning quality to be assessed first Classification indicators, referred to as the first level factor, by these index composing indexes classification layer, every class index is subdivided into certain general character Multiple the second level factors, these the second level factor composing indexes layers；It is denoted as set of factors U={ U₁,U₂,…,U_n, wherein U_iFor set of factors U In i-th of factor, U_iIt should meet

Step 2) construction fuzzy judgment matrix：The element c of judgment matrix_ijRepresent to be under the jurisdiction of the lower floor the of same upper strata element Relative importance between i element and j-th of element, c_ijValue (scale) scope for 1-9 natural number and they fall Number, c_ij=1/c_ji, numerical value is bigger to represent that relative to j-th element of i-th of element is more important, as shown in table 1；

The judgment matrix scale of table 1 and its implication

Triangle Fuzzy Evaluation Method applies Triangular Fuzzy Number, i.e., one determined by three numerals is used in judgment matrix Triangular function, instead of single numerical value employed in general evaluation method, to embody the mould of expert's opinion in multilevel iudge two-by-two Paste property；

Step 3) calculate obfuscation weight：To same group of important ratio compared with the different judges that multidigit expert makes, application The operational formula of Triangular Fuzzy Number is to two Triangular Fuzzy Number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂) computing, take it to count It is average, multiple fuzzy numbers are integrated into one, so as to form the fuzzy judgment matrix of a synthesis；

Step 4) de-fuzzy：For two fuzzy number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂), M₁≥M₂Possibility Degree, calculates a fuzzy number M_jMore than this layer other n-1 fuzzy number possibility degree namely the fuzzy number more than correspondence index power Weight, by normalized, can obtain final weight of the index in this layer, so as to characterize the power of this layer of each index weights distribution Weight vector；

Step 5) set up evaluate collection：Evaluation result is divided into λ grade, λ takes odd number, with reflected appraisal person to evaluation object The evaluation that may be made；Note evaluate collection is V=[V₁,V₂,…,V_λ]^T；

Step 6) multi-layer fuzzy comprehensive：To bottom set of factors U_i(i=1,2 ..., n) in each factor carry out Single factor test fuzzy evaluation, according to expert estimation, obtains factor U_ij(j=1,2 ..., m) to the degree of membership of each grade comment, so that It can obtain set of factors U_iSingle factor test fuzzy judgment matrix；

Using triangle Fuzzy Evaluation Method, set of factors U can obtain_iWeight vectors W_i=[w_i1,w_i2,…,w_in]^T, make one-level Fuzzy comprehensive evoluation, obtains factor U_iTo the degree of membership of each grade comment；

Ibid, simple element evaluation is carried out to other each layer set of factors, finally can obtain by judge object to each grade comment Degree of membership, so as to evaluation result.

In step 2) in, the membership function that described Triangular Fuzzy Number M is defined is as follows：

In above formula, l≤m≤u, l and u represent lower bound and the upper bound of the Triangular Fuzzy Number, and m represents the intermediate value that degree of membership is 1； General Triangular Fuzzy Number M is represented by (l, m, u).

In step 3) in, two described three fuzzy number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂) operation method such as Under：

M₁+M₂=(l₁+l₂,m₁+m₂,u₁+u₂) (2)

To same group of important ratio compared with the different judges that multidigit expert makes, using the computing of above-mentioned Triangular Fuzzy Number Formula, takes its arithmetic mean, and multiple fuzzy numbers are integrated into one, so as to form the fuzzy judgment matrix of a synthesis；

To kth layer element i fuzzy weighted values Di, computing formula is as follows

Wherein a_ijThe Triangular Fuzzy Number arranged for the i-th row jth in fuzzy judgment matrix, represents i-th of element relative to j-th The importance of element.

In step 4) in, it is described to two fuzzy number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂), M₁≥M₂Possibility Degree is defined as：

One fuzzy number M_jMore than this layer other n-1 fuzzy number possibility degree namely the fuzzy number more than correspondence index power Weight is：

w_cj'=ν (M >=M₁,M₂,…,M_n)=min ν (M >=M_i), i=1,2 ..., n (7)

By normalized, the final weight that can obtain the index in this layer is

So as to which the weight vectors for characterizing this layer of each index weights distribution are

W_i=[w₁,w₂,…,w_n]^T (9)

In step 6) in, described set of factors U_iSingle factor test fuzzy judgment matrix be：

Described factor U_iDegree of membership to each grade comment is

In formulaFor Fuzzy Arithmetic Operators.

The present invention uses analytic hierarchy process (AHP), and the influence of multiple factors is considered with reference to actual conditions, with very high theory Value and actual effect；Overall merit is carried out to programme using fuzzy synthetic appraisement method, optimal programme is determined.

Claims (5)

1. a kind of method for improving charging electric vehicle facilities planning quality, it is characterised in that：Described raising electric automobile fills The method of electric facilities planning quality includes the following steps performed in order：

Step 1) determine there is the classification influenceed to the scheme of raising charging electric vehicle facilities planning quality to be assessed first Index, referred to as the first level factor, by these index composing indexes classification layer, every class index is subdivided into the multiple of certain general character The second level factor, these the second level factor composing indexes layers；It is denoted as set of factors U={ U₁,U₂,…,U_n, wherein U_iFor in set of factors U I-th of factor, U_iIt should meet

Step 2) construction fuzzy judgment matrix：The element c of judgment matrix_ijRepresent to be under the jurisdiction of i-th of the lower floor of same upper strata element Relative importance between element and j-th of element, c_ijValue (scale) scope be 1-9 natural number and their inverse, c_ij=1/c_ji, numerical value is bigger to represent that relative to j-th element of i-th of element is more important, as shown in table 1；

The judgment matrix scale of table 1 and its implication

Triangle Fuzzy Evaluation Method applies Triangular Fuzzy Number, i.e., the triangle determined by three numerals is used in judgment matrix Shape function, instead of single numerical value employed in general evaluation method, to embody the ambiguity of expert's opinion in multilevel iudge two-by-two；

Step 3) calculate obfuscation weight：To same group of important ratio compared with the different judges that multidigit expert makes, using triangle The operational formula of fuzzy number is to two Triangular Fuzzy Number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂) computing, take it to count flat , multiple fuzzy numbers are integrated into one, so as to form the fuzzy judgment matrix of a synthesis；

Step 4) de-fuzzy：For two fuzzy number M₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂), M₁≥M₂Possibility degree, meter Calculate a fuzzy number M_jMore than this layer other n-1 fuzzy number possibility degree namely the fuzzy number more than correspondence index weight, warp Cross normalized, final weight of the index in this layer can be obtained, thus characterize the weight of this layer of each index weights distribution to Amount；

Step 5) set up evaluate collection：Evaluation result is divided into λ grade, λ takes odd number, may to evaluation object with reflected appraisal person The evaluation made；Note evaluate collection is V=[V₁,V₂,…,V_λ]^T；

Step 6) multi-layer fuzzy comprehensive：To bottom set of factors U_i(i=1,2 ..., n) in each factor carry out single factor test Fuzzy evaluation, according to expert estimation, obtains factor U_ij(j=1,2 ..., m) to the degree of membership of each grade comment, so that available Set of factors U_iSingle factor test fuzzy judgment matrix；

Using triangle Fuzzy Evaluation Method, set of factors U can obtain_iWeight vectors W_i=[w_i1,w_i2,…,w_in]^T, make one-level and obscure Comprehensive Evaluation, obtains factor U_iTo the degree of membership of each grade comment；

Ibid, simple element evaluation is carried out to other each layer set of factors, finally can obtain the person in servitude to each grade comment by judge object Category degree, so as to obtain evaluation result.

2. the method according to claim 1 for improving charging electric vehicle facilities planning quality, it is characterised in that：In step 2) in, the membership function that described Triangular Fuzzy Number M is defined is as follows：

${\mathrm{\μ}}_M\left(x\right)=\left\{\begin{array}{cc}\frac{1}{m-x}x-\frac{l}{m-l},& x\∈\[l,m\]\\ \frac{1}{m-u}x-\frac{u}{m-u},& x\∈\[m,u\]\\ 0,& otherwise\end{array}\right.---\left(1\right)$

In above formula, l≤m≤u, l and u represent lower bound and the upper bound of the Triangular Fuzzy Number, and m represents the intermediate value that degree of membership is 1；Typically Triangular Fuzzy Number M is represented by (l, m, u).

3. the method according to claim 1 for improving charging electric vehicle facilities planning quality, it is characterised in that：In step 3) in, two described three 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, different judges that multidigit expert makes, using the operational formula of above-mentioned Triangular Fuzzy Number, Its arithmetic mean is taken, multiple fuzzy numbers are integrated into one, so as to form the fuzzy judgment matrix of a synthesis；

To kth layer element i fuzzy weighted values Di, computing formula is as follows

$D_i=\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{a}_{ij}\÷\underset{i=1}{\overset{n}{\mathrm{\Σ}}}\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{a}_{ij},i=1,2,...n---\left(5\right)$

Wherein a_ijThe Triangular Fuzzy Number arranged for the i-th row jth in fuzzy judgment matrix, represents relative to j-th element of i-th of element Importance.

4. the method according to claim 1 for improving charging electric vehicle facilities planning quality, it is characterised in that：In step 4) it is described to two fuzzy number M in₁=(l₁,m₁,u₁), M₂=(l₂,m₂,u₂), M₁≥M₂Possibility degree be defined as：

$\mathrm{\ν}(M_1\≥M_2)=\left\{\begin{array}{cc}1,& m1>m2\\ \frac{l_2-u_1}{(m_1-u_1)-(m_2-l_2)},& m1\≤m2,u1\≥l2\\ 0,& otherwise\end{array}\right.---\left(6\right)$

One fuzzy number M_jMore than this layer other n-1 fuzzy number possibility degree namely the fuzzy number more than the weight of correspondence index be：

w_cj'=ν (M >=M₁,M₂,…,M_n)=min ν (M >=M_i), i=1,2 ..., n (7)

By normalized, the final weight that can obtain the index in this layer is

$w_{cj}={w_{cj}}^{\′}/\underset{i=1}{\overset{n}{\mathrm{\Σ}}}{w}_{ci}---\left(8\right)$

So as to which the weight vectors for characterizing this layer of each index weights distribution are

W_i=[w₁,w₂,…,w_n]^T (9)。

5. the method according to claim 1 for improving charging electric vehicle facilities planning quality, it is characterised in that：In step 6) in, described set of factors U_iSingle factor test fuzzy judgment matrix be：

Described factor U_iDegree of membership to each grade comment is

In formulaFor Fuzzy Arithmetic Operators.