CN109858765A - EV charger integrated evaluating method and device based on TOPSIS method - Google Patents
EV charger integrated evaluating method and device based on TOPSIS method Download PDFInfo
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Abstract
The present invention relates to a kind of EV charger integrated evaluating methods and device based on TOPSIS method, its technical characterstic is: the following steps are included: step 1, according to electric car itself Static State Index and power grid interacting dynamic indicator, establishing Multi-layer electric charger for automobile operating status index system；Step 2 carries out subjective analysis to each index significance level, and the weight of each layer index is calculated with analytic hierarchy process (AHP)；Step 3 optimizes subjective weight using Evaluation formula, forms combining weights；Step 4 is given a mark and is sorted to evaluation object using TOPSIS method, determines the superiority and inferiority of charger operating status.The present invention can comprehensively evaluate the performance of electric automobile battery charger, and the selection for electric car charging provides foundation, meet physical planning in the process to the requirements of type selecting of electric automobile battery charger.
Description
Technical field
The invention belongs to technical field of power systems, are related to electric automobile battery charger integrated evaluating method and device, especially
It is a kind of EV charger integrated evaluating method and device based on TOPSIS method.
Background technique
In recent years, electric car protects environment etc. to have very big as a kind of new traffic tool in energy-saving and emission-reduction
Advantage, therefore become national and each grid company and give priority to object.Necessary corollary equipment of the charger as electric car,
Also the favor in market is received therewith, there is the growth advanced by leaps and bounds in quantity.However, charger model at present on the market is huge
Mostly complicated, quality and spread in performance are uneven, are only evaluated charger and filter out high-quality charger to promote, could promoted
Develop considerablely into electric car.Therefore, it is necessary to combine certain evaluation index and evaluation method, objective to charger progress,
It evaluates comprehensive, scientifically.
Summary of the invention
It is an object of the invention to overcome the deficiencies in the prior art, propose that a kind of EV charger based on TOPSIS method is comprehensive
Evaluation method and device can obtain comprehensively and effectively charger evaluation result, mention for the comparison evaluation and test of electric automobile battery charger
For foundation.
The present invention solves its realistic problem and adopts the following technical solutions to achieve:
A kind of EV charger integrated evaluating method based on TOPSIS method, comprising the following steps:
Step 1 interacts dynamic indicator according to electric car itself Static State Index and power grid, establishes the charging of Multi-layer electric automobile
Machine operating status index system；
Step 2 carries out subjective analysis to each index significance level, and the weight of each layer index is calculated with analytic hierarchy process (AHP)；
Step 3 optimizes subjective weight using Evaluation formula, forms combining weights；
Step 4 is given a mark and is sorted to evaluation object using TOPSIS method, determines the superiority and inferiority of charger operating status；
Moreover, the step 1 establishes Multi-layer electric charger for automobile operating status index system are as follows:
Electric automobile battery charger static evaluation index includes output performance index, safe performance indexes, Electro Magnetic Compatibility
Index and other performance indicators；
Electric automobile battery charger dynamic assessment index includes separate unit charger interaction performance indicator and the interaction of Duo Tai charger
Performance indicator.
Moreover, the specific steps of the weight for calculating each layer index with analytic hierarchy process (AHP) of the step 2 include:
(1) according to index property, destination layer, rule layer and solution layer three-decker are established；
(2) the n*n comparator matrix A that each index compares two-by-two is established,
In formula: A is comparator matrix, aijIt is i-th of factor in this layer to the significance level of j-th of factor；On leading diagonal
Value perseverance be 1；
(3) to comparing its characteristic root of Matrix Solving | λ E-A |=0, it solves and show that the Maximum characteristic root of comparator matrix is λmax:
|A-λmaxE | x=0
Its corresponding feature vector is obtained, respective weights can be obtained after normalization；
(4) all factors of bottom time are calculated for the weight of high-rise relative importance:
In formula, wiFor the weight of bottom index i, wkiFor the weight of the upper layer index of number of plies k where bottom index i.
Moreover, the specific steps of the step 3 include:
(1) for two different weight W1And W2, consistency check is carried out using distance function:
In formula: w1jFor j-th of weighted value in first weight vectors group, w2jFor j-th of power in second weight vectors group
Weight values；
As d (W1,W2When) < 0.1, it is believed that W1With W2It is closer to, it can be with combination weighting；
(2) weight optimization objective function is established, i.e., with W* to W1And W2Deviation minimization:
Wherein:W*For a kind of possible weight sets, λi *For i-th of weight sets weight because
Son, WiFor i-th of weight sets；
(3) weight is carried out according to formula and solves λ1 *,λ2 *Afterwards, it is corresponding that i-th of weight sets is obtained after being normalized
Weight factor λi:
(4) final combining weights are as follows:
Moreover, the specific steps of the step 4 include:
(1) each index utility function has the characteristics that monotonicity, and index is divided into more bigger more excellent type index and smaller more excellent type
Index, and nondimensionalization processing is carried out to different type index:
For more bigger more excellent type index:
For smaller more excellent type index:
In formula: vijFor the processing costs of i-th of evaluation object, j-th of index, xijFor i-th of evaluation object, j-th of index
Original value, min (xj) be j-th of index minimum value, max (xj) be j-th of index maximum value；
(2) evaluations matrix is multiplied into combining weights matrix and obtains weighting evaluation matrix:
Wherein:
fij=vij×wj
In formula: wiIt is the weight of j-th of index, fijFor under j-th of index, the weighting evaluation value of i-th of evaluation object；
(3) optimal value for searching out each column is denoted asThe worst-case value of each column is denoted as fj^, thenFor optimal solution vector, F^=[f1^,f2^,…,fn^] it is most inferior solution vector；
(4) Euclidean distance of each evaluation object and optimal vector and most bad vector is calculated:
In formula, Si *For the Euclidean distance of i-th of evaluation object and optimal solution, Si^ is i-th of evaluation object and most inferior solution
Euclidean distance；
(5) the opposite close to degree of each evaluation object is calculated:
In formula, Ci *For the opposite close to degree of i-th evaluation object；
(6) it sorts according to close to degree height to each evaluation object superiority and inferiority degree, divided rank provides evaluation.
A kind of electric automobile battery charger evaluation of running status device based on TOPSIS method includes obtaining module, computing module
And sorting module；
The acquisition module, for obtaining each supplemental characteristic of electric automobile battery charger；
The computing module, for the evaluation index result of each charger to be calculated according to obtained parameter；
The sorting module arranges electric automobile battery charger for calculating gained evaluation index according to computing module
Sequence simultaneously provides evaluation result.
The advantages of the present invention:
1, the present invention (step 1) when establishing electric car comprehensive evaluation index, not only allows for electric automobile battery charger
Static State Index, it is also contemplated that the dynamic indicator that charger is interacted with power grid keeps evaluation index more comprehensive specific.
2, the present invention (step 3) when determining each sub- index weights uses Evaluation formula.The comprehensive master of the weight obtained
The shortcomings that seeing weight and the advantages of objective weight, and can evading subjective weight and objective weight, keeps evaluation weight more reasonable.
3, the present invention has selected TOPSIS method (step 4) in terms of evaluation method, so that evaluation result is accurately quick, with
Actually it is consistent.
Detailed description of the invention
Fig. 1 is process flow diagram of the invention；
Fig. 2 is the structural representation of the electric automobile battery charger evaluation of running status device of the invention based on TOPSIS method
Figure.
Specific embodiment
The embodiment of the present invention is described in further detail below in conjunction with attached drawing:
A kind of electric automobile battery charger integrated evaluating method based on TOPSIS method, as shown in Figure 1, comprising the following steps:
Step 1 interacts dynamic indicator according to electric car itself Static State Index and power grid, establishes the charging of Multi-layer electric automobile
Machine operating status index system；
The step 1 establishes Multi-layer electric charger for automobile operating status index system are as follows:
Electric automobile battery charger static evaluation index includes output performance index, safe performance indexes, Electro Magnetic Compatibility
Index and other performance indicators；
Electric automobile battery charger dynamic assessment index includes separate unit charger interaction performance indicator and the interaction of Duo Tai charger
Performance indicator.
Step 2 carries out subjective analysis to each index significance level, and the weight of each layer index is calculated with analytic hierarchy process (AHP)；
The specific steps of the weight for calculating each layer index with analytic hierarchy process (AHP) of the step 2 include:
(1) according to index property, destination layer, rule layer and solution layer three-decker are established；
(2) the n*n comparator matrix A that each index compares two-by-two is established,
In formula: A is comparator matrix, aijIt is i-th of factor in this layer to the significance level of j-th of factor；On leading diagonal
Value perseverance be 1；
(3) to comparing its characteristic root of Matrix Solving | λ E-A |=0, it solves and show that the Maximum characteristic root of comparator matrix is λmax:
|A-λmaxE | x=0
Its corresponding feature vector is obtained, respective weights can be obtained after normalization；
(2) all factors of bottom time are calculated for the weight of high-rise relative importance.
In formula, wiFor the weight of bottom index i, wkiFor the weight of the upper layer index of number of plies k where bottom index i.
Step 3 optimizes subjective weight using Evaluation formula, forms combining weights；
The specific steps of the step 3 include:
(1) for two different weight W1And W2, consistency check is carried out using distance function:
In formula: w1jFor j-th of weighted value in first weight vectors group, w2jFor j-th of power in second weight vectors group
Weight values；
As d (W1,W2When) < 0.1, it is believed that W1With W2It is closer to, it can be with combination weighting；
(2) weight optimization objective function is established, i.e., with W*To W1And W2Deviation minimization:
Wherein:W*For a kind of possible weight sets, λi *For the weight factor of i-th of weight sets,
WiFor i-th of weight sets；
(3) weight is carried out according to formula and solves λ1 *,λ2 *Afterwards, it is corresponding that i-th of weight sets is obtained after being normalized
Weight factor λi:
(4) final combining weights are as follows:
Step 4 is given a mark and is sorted to evaluation object using TOPSIS method, determines the superiority and inferiority of charger operating status；
The specific steps of the step 4 include:
(3) each index utility function has the characteristics that monotonicity, and index is divided into more bigger more excellent type index and smaller more excellent type
Index, and nondimensionalization processing is carried out to different type index:
For more bigger more excellent type index:
For smaller more excellent type index:
In formula: vijFor the processing costs of i-th of evaluation object, j-th of index, xijFor i-th of evaluation object, j-th of index
Original value, min (xj) be j-th of index minimum value, max (xj) be j-th of index maximum value；
(2) evaluations matrix is multiplied into combining weights matrix and obtains weighting evaluation matrix:
Wherein:
fij=vij×wj
In formula: wiIt is the weight of j-th of index, fijFor under j-th of index, the weighting evaluation value of i-th of evaluation object；
(3) optimal value for searching out each column is denoted asThe worst-case value of each column is denoted as fj^, thenFor optimal solution vector, F^=[f1^,f2^,…,fn^] it is most inferior solution vector；
(4) Euclidean distance of each evaluation object and optimal vector and most bad vector is calculated:
In formula, Si *For the Euclidean distance of i-th of evaluation object and optimal solution, Si^ is i-th of evaluation object and most inferior solution
Euclidean distance；
(5) the opposite close to degree of each evaluation object is calculated:
In formula, Ci *For the opposite close to degree of i-th evaluation object；
(6) it sorts according to close to degree height to each evaluation object superiority and inferiority degree, divided rank provides evaluation.
A kind of electric automobile battery charger evaluation of running status device based on TOPSIS method, includes: acquisition mould as shown in Figure 2
Block, computing module and sorting module；
The acquisition module, for obtaining each supplemental characteristic of electric automobile battery charger；
The computing module, for the evaluation index result of each charger to be calculated according to obtained parameter；
The sorting module arranges electric automobile battery charger for calculating gained evaluation index according to computing module
Sequence simultaneously provides evaluation result.
In embodiment provided herein, it should be understood that disclosed method and apparatus can pass through others
Mode is realized.For example, device implementation column described above is only schematical, for example, the division of the unit, only
A kind of logical function partition, there may be another division manner in actual implementation, for example, multiple units or components can combine or
Person is desirably integrated into another system, or some features can be ignored, or does not execute.Another point, shown or discussed is mutual
Between coupling, direct-coupling or communication connection can be through some communication interfaces, the INDIRECT COUPLING or logical of device or unit
Letter connection can be electrical property, mechanical or other forms.
The unit as illustrated by the separation member may or may not be physically separated, aobvious as unit
The component shown may or may not be physical unit, it can and it is in one place, or may be distributed over multiple
In network unit.It can select some or all of unit therein according to the actual needs to realize the mesh of this embodiment scheme
's.In addition, the functional units in various embodiments of the present invention may be integrated into one processing unit, is also possible to each
Unit physically exists alone, and can also be integrated in one unit with two or more units.
It, can be with if the function is realized in the form of SFU software functional unit and when sold or used as an independent product
It is stored in a computer readable storage medium.Based on this understanding, technical solution of the present invention is substantially in other words
The part of the part that contributes to existing technology or the technical solution can be embodied in the form of software products, the meter
Calculation machine software product is stored in a storage medium, including some instructions are used so that a computer equipment (can be a
People's computer, server, or network equipment etc.) it performs all or part of the steps of the method described in the various embodiments of the present invention.
And storage medium above-mentioned includes: that USB flash disk, mobile hard disk, read-only memory (ROM, Read-0nly Memory), arbitrary access are deposited
The various media that can store program code such as reservoir (RAM, Random Access Memory), magnetic or disk.
The foregoing description of the disclosed embodiments enables those skilled in the art to implement or use the present invention.
Any modifications, equivalent substitutions and improvements etc. made within spiritual principles of the invention, should be included in power of the invention
Within the scope of benefit is claimed.
Claims (6)
1. a kind of EV charger integrated evaluating method based on TOPSIS method, it is characterised in that: the following steps are included:
Step 1 interacts dynamic indicator according to electric car itself Static State Index and power grid, establishes Multi-layer electric charger for automobile fortune
Row state index system；
Step 2 carries out subjective analysis to each index significance level, and the weight of each layer index is calculated with analytic hierarchy process (AHP)；
Step 3 optimizes subjective weight using Evaluation formula, forms combining weights；
Step 4 is given a mark and is sorted to evaluation object using TOPSIS method, determines the superiority and inferiority of charger operating status.
2. a kind of EV charger integrated evaluating method based on TOPSIS method according to claim 1, it is characterised in that: institute
That states step 1 establishes Multi-layer electric charger for automobile operating status index system are as follows:
Electric automobile battery charger static evaluation index includes output performance index, safe performance indexes, Electro Magnetic Compatibility index
With other performance indicators；
Electric automobile battery charger dynamic assessment index includes separate unit charger interaction performance indicator and Duo Tai charger interaction performance
Index.
3. a kind of EV charger integrated evaluating method based on TOPSIS method according to claim 1, it is characterised in that: institute
The specific steps for stating the weight for calculating each layer index with analytic hierarchy process (AHP) of step 2 include:
(1) according to index property, destination layer, rule layer and solution layer three-decker are established；
(2) the n*n comparator matrix A that each index compares two-by-two is established,
In formula: A is comparator matrix, aijIt is i-th of factor in this layer to the significance level of j-th of factor；Value on leading diagonal
Perseverance is 1；
(3) to comparing its characteristic root of Matrix Solving | λ E-A |=0, it solves and show that the Maximum characteristic root of comparator matrix is λmax:
|A-λmaxE | x=0
Its corresponding feature vector is obtained, respective weights can be obtained after normalization；
(4) all factors of bottom time are calculated for the weight of high-rise relative importance:
In formula, wiFor the weight of bottom index i, wkiFor the weight of the upper layer index of number of plies k where bottom index i.
4. a kind of EV charger integrated evaluating method based on TOPSIS method according to claim 1, it is characterised in that: institute
The specific steps for stating step 3 include:
(1) for two different weight W1And W2, consistency check is carried out using distance function:
In formula: w1jFor j-th of weighted value in first weight vectors group, w2jFor j-th of weighted value in second weight vectors group；
As d (W1,W2When) < 0.1, it is believed that W1With W2It is closer to, it can be with combination weighting；
(2) weight optimization objective function is established, i.e., with W*To W1And W2Deviation minimization:
Wherein:W*For a kind of possible weight sets, λi *For the weight factor of i-th of weight sets, WiFor
I-th of weight sets；
(3) weight is carried out according to formula and solves λ1 *,λ2 *Afterwards, the corresponding weight of i-th of weight sets is obtained after being normalized
Factor lambdai:
(4) final combining weights are as follows:
5. a kind of EV charger integrated evaluating method based on TOPSIS method according to claim 1, it is characterised in that: institute
The specific steps for stating step 4 include:
(1) each index utility function has the characteristics that monotonicity, and index is divided into more bigger more excellent type index and smaller more excellent type index,
And nondimensionalization processing is carried out to different type index:
For more bigger more excellent type index:
For smaller more excellent type index:
In formula: vijFor the processing costs of i-th of evaluation object, j-th of index, xijFor the original of i-th of evaluation object, j-th of index
Value, min (xj) be j-th of index minimum value, max (xj) be j-th of index maximum value；
(2) evaluations matrix is multiplied into combining weights matrix and obtains weighting evaluation matrix:
Wherein:
fij=vij×wj
In formula: wiIt is the weight of j-th of index, fijFor under j-th of index, the weighting evaluation value of i-th of evaluation object；
(3) optimal value for searching out each column is denoted asThe worst-case value of each column is denoted as fj^, then
For optimal solution vector, F^=[f1^,f2^,…,fn^] it is most inferior solution vector；
(4) Euclidean distance of each evaluation object and optimal vector and most bad vector is calculated:
In formula, Si *For the Euclidean distance of i-th of evaluation object and optimal solution, SiIt is European with most inferior solution that ^ is i-th evaluation object
Distance；
(5) the opposite close to degree of each evaluation object is calculated:
In formula, Ci *For the opposite close to degree of i-th evaluation object；
(6) it sorts according to close to degree height to each evaluation object superiority and inferiority degree, divided rank provides evaluation.
6. a kind of EV charger overall merit side based on TOPSIS method as described in any one of claim 1 to 5 claim
The evaluating apparatus of method includes obtaining module, computing module and sorting module；
The acquisition module, for obtaining each supplemental characteristic of electric automobile battery charger；
The computing module, for the evaluation index result of each charger to be calculated according to obtained parameter；
The sorting module is ranked up simultaneously electric automobile battery charger for calculating gained evaluation index according to computing module
Provide evaluation result.
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| CN110400047A (en) * | 2019-06-18 | 2019-11-01 | 上海电器科学研究所（集团）有限公司 | A kind of integrated evaluating method of electric car charging network operation |
| CN111275353A (en) * | 2020-02-14 | 2020-06-12 | 杭州电子科技大学 | Electric vehicle charging distribution method based on rated capacity of distribution transformer |
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| CN111949939A (en) * | 2020-08-26 | 2020-11-17 | 北京航空航天大学 | Intelligent electric meter running state evaluation method based on improved TOPSIS and cluster analysis |
| CN113449949A (en) * | 2021-03-09 | 2021-09-28 | 国网浙江省电力有限公司湖州供电公司 | Power equipment evaluation method based on empowerment rating combination algorithm |
| CN113487197A (en) * | 2021-07-12 | 2021-10-08 | 吉林大学 | TOPSIS (technique for order preference by similarity to Ideal solution) evaluation model-based vehicle networking information screening method |
| CN114513744A (en) * | 2021-07-07 | 2022-05-17 | 南京航空航天大学 | Channel state evaluation method based on position information |
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Application publication date: 20190607 |