CN104573897A - Method and device for evaluating power distribution network planning - Google Patents

Abstract

The invention discloses a method and a device for evaluating power distribution network planning. The method for evaluating power distribution network planning comprises the following steps: receiving a plurality of initial evaluation values of each index in multiple indexes of the power distribution network planning to obtain an evaluation matrix of the multiple indexes; adopting a predetermined function to process the evaluation matrix to obtain a weight matrix of the evaluation matrix; calculating the weight of each index; calculating the target evaluation value of each index according to the weight matrix and the weight of each index. Through the method and the device, the problem that power network planning cannot be evaluated as a whole in the prior art is solved, so that the power network planning can be evaluated as a whole, and then the effect of improving the evaluation guidance for the power network planning is reached.

Description

The appraisal procedure of distribution network planning and device

Technical field

The present invention relates to electric power distribution field, in particular to a kind of appraisal procedure and device of distribution network planning.

Background technology

The planning appraisal of power distribution network refers to that the characteristic for power distribution network different aspect selects corresponding evaluation form, and by certain evaluation method, multiple assessment factor or evaluation index is converted into the information that can reflect power distribution network general status.Electric power system is contact power supply and user, carries and the important step of distributing electric energy to user.When power supply reliability refers to that grid equipment is stopped transport, to the degree of reliability that user powers continuously.Power distribution network is positioned at electric system end, as electric power system to a ring important and complicated in customer power supply, has vital effect to power supply reliability.Research both at home and abroad in distribution network planning reliability assessment achieves certain achievement, and the evaluation work of power network planning scheme also receives increasing attention simultaneously, and defines certain achievement.

First traditional planning evaluate alternatives is based on technical consideration, using technical indicators such as reliabilities as the test condition that must meet, chooses investment cost those at least on this basis again as optimal case.This traditional evaluation thinking does not quantize technical indicators such as reliabilities, and the operation maintenance cost in less consideration later stage, therefore cannot realize the economy of programme and the coordination of reliability.In addition, other appraisal procedure such as least cost appraisal procedure, income/assessment of cost method etc. all do not consider the requirement of reliability.Traditional power distribution network assessment mainly comprises the assessment of the single indexs such as reliability evaluation, Economic Evaluation, safety evaluatio, power supply quality evaluation, these assessments have rated the operation level of power distribution network from different aspect, but fail to provide the evaluation of globality, not strong to the guide of the actual construction of electrical network.

For the problem cannot assessing Electric Power Network Planning in correlation technique on the whole, at present effective solution is not yet proposed.

Summary of the invention

The invention provides a kind of appraisal procedure and device of distribution network planning, to solve the problem cannot assessing Electric Power Network Planning in prior art on the whole.

To achieve these goals, according to an aspect of the present invention, provide a kind of appraisal procedure of Electric Power Network Planning, comprising: the multiple initial assessment values receiving each index in distribution network planning many index, obtain the evaluating matrix of many index; Adopt predefined function process evaluating matrix, obtain the weight matrix of evaluating matrix; Calculate the weight of each index; And the goal-based assessment value of each index of weight calculation according to weight matrix and each index.

Further, predefined function comprises multiple predetermined white function, adopt pre-defined function process evaluating matrix, the weight matrix obtaining evaluating matrix comprises: from multiple white function, be respectively each choose targets predetermined white function, wherein, the predetermined white function for different choose targets is identical or different; And according to following formulae discovery evaluating matrix $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Weight matrix $R=\left[\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ r_{r1}& r_{r2}& ...& r_{\mathrm{rn}}\end{array}\right]:$

$r_{\mathrm{sj}}=\frac{f_i\left(l_{\mathrm{sj}}\right)}{\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{f}_i\left(l_{\mathrm{sj}}\right)},$

Wherein, l _sjfor s assessed value of jth item index in many index, f _i(l _sj) be function f _ix in (), independent variable x value is l _sjtime corresponding functional value, f _ix () is the predetermined white function of jth item choose targets, r _sjfor s weights of jth item index, and m, n and r are the natural number of more than 2, and s gets 1 to r successively, and j gets 1 to n successively.

Further, the weight calculating each index comprises: according to formula ${\mathrm{\ξ}}_j\left(s\right)=\frac{\underset{j}{\min }\underset{s}{\min }|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}{|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}$ Compute associations coefficient, wherein l _maxs=max{l _s1, l _s2..., l _sr, ρ is for presetting resolution coefficient; Calculate the sequence α of each index _j; And according to formula $w_j=\frac{\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)}{\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)\right)}$ Calculate the weight of each index, wherein, w _jfor the weight of jth item index.

Further, the sequence α of each index is calculated _jcomprise: according to piecewise function $a_{\mathrm{sj}}=\left\{\begin{array}{cc}0& l_{\mathrm{sj}}\∈\left(\mathrm{0,0.1}\right)\\ \frac{1}{\mathrm{int}(l_{\mathrm{sj}}\×10)}& l_{\mathrm{sj}}\∈\left[\mathrm{0.1,1}\right)\\ \mathrm{int}\left(l_{\mathrm{sj}}\right)& l_{\mathrm{sj}}\∈\left[\mathrm{1,10}\right)\\ 9& l_{\mathrm{sj}}\∈[10,+\∞)\end{array}\right.$ To matrix $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Each element carry out process and obtain matrix $A=\left[\begin{array}{cccc}{a}_{11}& a_{12}& ...& a_{1n}\\ a_{21}& a_{22}& ...& a_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ a_{r1}& a_{r2}& ...& a_{\mathrm{rn}}\end{array}\right];$ To each element piecewise function of matrix A process, obtain matrix $\mathrm{\μ}=\left[\begin{array}{cccc}{\mathrm{\μ}}_{11}& {\mathrm{\μ}}_{12}& ...& {\mathrm{\μ}}_{1n}\\ {\mathrm{\μ}}_{21}& {\mathrm{\μ}}_{22}& ...& {\mathrm{\μ}}_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ {\mathrm{\μ}}_{r1}& {\mathrm{\μ}}_{r2}& ...& {\mathrm{\μ}}_{\mathrm{rn}}\end{array}\right];$ And according to formula ${\mathrm{\α}}_j=\frac{2}{n(n-1)}\underset{i=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\μ}}_{\mathrm{ij}}$ Calculate sequence, wherein, int is rounding operation, $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_j=1.$

Further, the goal-based assessment value according to each index of weight calculation of weight matrix and each index comprises: the goal-based assessment value calculating each index according to formula B=WR, wherein, and W=(w ₁w ₂w _n), B is the set of the goal-based assessment value of each index.

Further, after the goal-based assessment value of each index of weight calculation according to weight matrix and each index, appraisal procedure also comprises: receive first and preset set V=(v ₁, v ₂..., v _m); Calculate first and preset element v in set _ipoint value of evaluation d _i; According to formula Z=BD ^tcalculate the score value of distribution network planning, wherein, D ^t=(d ₁d ₂d _m) ^t, Z is the point value of evaluation of distribution network planning; And compare distribution network planning score value and first preset gather, draw the evaluation grade of distribution network planning.

Further, multiple predetermined white function comprises: upper class morphic function, middle class morphic function and lower class morphic function, wherein,

The function expression of upper class morphic function is $f_1\left(x\right)=\left\{\begin{array}{cc}\frac{x}{l_1}& x\∈[0,l_1]\\ 1& x\∈[l_1,\∞)\\ 0& x\∈(-\∞,0)\end{array}\right.,$

The function expression of middle class morphic function is $f_2\left(x\right)=\left\{\begin{array}{cc}\frac{x}{l_1}& x\∈[0,l_1]\\ 2-\frac{x}{l_1}& x\∈[l_1,2l_1]\\ 0& x\∉\left(\mathrm{0,2}{l}_1\right]\end{array}\right.,$

The function expression of lower class morphic function is $f_3\left(x\right)=\left\{\begin{array}{cc}1& x\∈[0,l_1]\\ \frac{l_2-x}{l_2-l_1}& x\∈[l_1,l_2]\\ 0& x\∉(0,l_2]\end{array}\right.,$

Wherein, l ₁and l ₂value be preset value.

To achieve these goals, according to another aspect of the present invention, provide a kind of apparatus for evaluating of Electric Power Network Planning, comprising: the first receiving element, for receiving multiple initial assessment values of each index in distribution network planning many index, obtain the evaluating matrix of many index; Processing unit, for adopting predefined function process evaluating matrix, obtains the weight matrix of evaluating matrix; First computing unit, for calculating the weight of each index; And second computing unit, for the goal-based assessment value of each index of weight calculation according to weight matrix and each index.

Further, predefined function comprises multiple predetermined white function, and processing unit comprises: chooser unit, is respectively each choose targets predetermined white function from multiple white function, wherein, the predetermined white function for different choose targets is identical or different; And first computation subunit: for according to following formulae discovery evaluating matrix $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Weight matrix $R=\left[\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ r_{r1}& r_{r2}& ...& r_{\mathrm{rn}}\end{array}\right]:$

$r_{\mathrm{sj}}=\frac{f_i\left(l_{\mathrm{sj}}\right)}{\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{f}_i\left(l_{\mathrm{sj}}\right)},$

Wherein, l _sjfor s assessed value of jth item index in many index, f _i(l _sj) be function f _ix in (), independent variable x value is l _sjtime corresponding functional value, f _ix () is the predetermined white function of jth item choose targets, r _sjfor s weights of jth item index, and m, n and r are the natural number of more than 2, and s gets 1 to r successively, and j gets 1 to n successively.

Further, the first computing unit comprises: the second computation subunit, for according to formula ${\mathrm{\ξ}}_j\left(s\right)=\frac{\underset{j}{\min }\underset{s}{\min }|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}{|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}$ Compute associations coefficient, wherein l _maxs=max{l _s1, l _s2..., l _sr, ρ is for presetting resolution coefficient; 3rd computation subunit, for calculating the sequence α of each index _j; And the 4th computation subunit, for according to formula $w_j=\frac{\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)}{\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)\right)}$ Calculate the weight of each index, wherein, w _jfor the weight of jth item index.

Further, the 3rd computation subunit comprises: the first processing module, for according to piecewise function $a_{\mathrm{sj}}=\left\{\begin{array}{cc}0& l_{\mathrm{sj}}\∈\left(\mathrm{0,0.1}\right)\\ \frac{1}{\mathrm{int}(l_{\mathrm{sj}}\×10)}& l_{\mathrm{sj}}\∈\left[\mathrm{0.1,1}\right)\\ \mathrm{int}\left(l_{\mathrm{sj}}\right)& l_{\mathrm{sj}}\∈\left[\mathrm{1,10}\right)\\ 9& l_{\mathrm{sj}}\∈[10,+\∞)\end{array}\right.$ To matrix $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Each element carry out process and obtain matrix $A=\left[\begin{array}{cccc}{a}_{11}& a_{12}& ...& a_{1n}\\ a_{21}& a_{22}& ...& a_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ a_{r1}& a_{r2}& ...& a_{\mathrm{rn}}\end{array}\right];$ Second processing module, for piecewise function each element of matrix A is processed, obtains matrix $\mathrm{\μ}=\left[\begin{array}{cccc}{\mathrm{\μ}}_{11}& {\mathrm{\μ}}_{12}& ...& {\mathrm{\μ}}_{1n}\\ {\mathrm{\μ}}_{21}& {\mathrm{\μ}}_{22}& ...& {\mathrm{\μ}}_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ {\mathrm{\μ}}_{r1}& {\mathrm{\μ}}_{r2}& ...& {\mathrm{\μ}}_{\mathrm{rn}}\end{array}\right];$ And computing module, for according to formula ${\mathrm{\α}}_j=\frac{2}{n(n-1)}\underset{i=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\μ}}_{\mathrm{ij}}$ Calculate sequence, wherein, int is rounding operation, $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_j=1.$

Further, the second computing unit comprises: the 5th computation subunit, for calculating the goal-based assessment value of each index according to formula B=WR, wherein, and W=(w ₁w ₂w _n), B is the set of the goal-based assessment value of each index.

Further, apparatus for evaluating also comprises: the second receiving element, presets set for receiving first; 3rd computing unit, presets element v in set for calculating first _ipoint value of evaluation d _j; 4th computing unit, for according to formula Z=BD ^tcalculate the score value of distribution network planning, wherein, D ^t=(d ₁, d ₂..., d _m) ^t, Z is the point value of evaluation of distribution network planning; And comparing unit, score value and first for comparing distribution network planning are preset and are gathered, and draw the evaluation grade of distribution network planning.

The present invention adopts the multiple initial assessment values receiving each index in distribution network planning many index, obtains the evaluating matrix of many index; Adopt predefined function process evaluating matrix, obtain the weight matrix of evaluating matrix; Calculate the weight of each index; And the goal-based assessment value of each index of weight calculation according to weight matrix and each index.Multiple assessed value is provided by each index in the multiple indexs to the assessment electrical network formulated, determine evaluating matrix, and the weight matrix of evaluating matrix is calculated according to evaluating matrix, calculate the weight of each index, and assess Electric Power Network Planning by the method for the assessed value of each evaluation index of weight matrix meter, obtain assessing the valuation of each quantification of targets in electricity planning.Multiple assessment factor or evaluation index are converted into the information incorporated that can reflect electrical network general status, solve the problem cannot assessing Electric Power Network Planning in prior art on the whole, thus can assessment Electric Power Network Planning on the whole, reach the effect of the directiveness improving Electric Power Network Planning assessment.

Accompanying drawing explanation

The accompanying drawing forming a application's part is used to provide a further understanding of the present invention, and schematic description and description of the present invention, for explaining the present invention, does not form inappropriate limitation of the present invention.In the accompanying drawings:

Fig. 1 is the process flow diagram of the appraisal procedure of distribution network planning according to the embodiment of the present invention;

Fig. 2 a to Fig. 2 c is the function curve diagram of the three kinds of white functions used according to the appraisal procedure of the distribution network planning of the embodiment of the present invention;

Fig. 3 is the schematic diagram of apparatus for evaluating of the distribution network planning according to the invention process row; And

Fig. 4 is the schematic diagram of the apparatus for evaluating of distribution network planning according to the preferred embodiment of the invention.

Embodiment

It should be noted that, when not conflicting, the embodiment in the application and the feature in embodiment can combine mutually.Below with reference to the accompanying drawings and describe the present invention in detail in conjunction with the embodiments.

Fig. 1 is the process flow diagram of the appraisal procedure of distribution network planning according to the embodiment of the present invention, and as shown in Figure 1, the method comprises following step S102 to step S108:

S102: the multiple initial assessment values receiving each index in distribution network planning many index, obtain the evaluating matrix of many index.Particularly, before assessment Electric Power Network Planning, first formulate the index of assessment Electric Power Network Planning, the assessment experts of multidigit Electric Power Network Planning provides assessed value respectively to each index, obtains evaluating matrix.The index of Electric Power Network Planning assessment comprises the index of the various aspects of Electric Power Network Planning, as reliability, economy, adaptability, harmony, user satisfaction etc.

S104: adopt predefined function process evaluating matrix, obtain the weight matrix of evaluating matrix.Particularly, each element adopting Grey Statistical method to calculate evaluating matrix belongs to the weights of each evaluation grade: from multiple white function, select a predetermined white function as the function processed the assessed value of this index according to the value distribution of each index respectively, and obtain the weight matrix of evaluating matrix according to each element of selected white function process evaluating matrix.

S106: the weight calculating each index.Particularly, development of judgment matrix, utilizes AHM method to calculate the relative order of evaluation index.Utilize evaluating matrix to calculate the correlation coefficient of each index, thus calculate the degree of association.The weight of each index is obtained again by the relative order of each index and calculation of relationship degree.

S108: according to the goal-based assessment value of each index of weight calculation of weight matrix and each index.Particularly, the row matrix that the goal-based assessment value that the row matrix that forms of the weight of each index and the product of weight matrix are each evaluation index is formed.What this row matrix reflected is the score of each index in whole Electric Power Network Planning.

The appraisal procedure of the distribution network planning of the embodiment of the present invention, multiple assessed value is provided by each index in the multiple indexs to the assessment electrical network formulated, determine evaluating matrix, and the weight matrix of evaluating matrix is calculated according to evaluating matrix, calculate the weight of each index, and assess Electric Power Network Planning by the method for the assessed value of each evaluation index of weight matrix meter, obtain assessing the valuation of each quantification of targets in electricity planning.Multiple assessment factor or evaluation index are converted into the information incorporated that can reflect electrical network general status, solve the problem cannot assessing Electric Power Network Planning in prior art on the whole, thus can assessment Electric Power Network Planning on the whole, reach the effect of the directiveness improving Electric Power Network Planning assessment.

Further, the present invention, has because usually formulating the index of assessment electrical network particularly according to reliability, economy, adaptability, harmony and user satisfaction: the degrees of coordination that the average power off time of system, system on average stop level rate, the average power off time of user, user on average stop level rate, power supply and electricity consumption in the time limit, capacity-load ratio, load margin, main distribution coordination and region are regained in construction investment expense, operation and maintenance cost, energy loss expense, interruption cost, sale of electricity net proceeds, investment and user are to the satisfaction of resource and environment.

Electrical network is positioned at the end of whole electric power system, and vital effect is played in the normal operation of reliability to electric power system of electrical network, but rational planning and design should consider the correlative factors such as economy, adaptability, harmony and user satisfaction equally.Desirable Electric Power Network Planning should be when ensureing electric network reliability, make that power grid construction is invested, running cost is minimum, the coordination ability of electrical network is the highest, the satisfaction of user is also higher, but in the Electric Power Network Planning process of reality, these conditions can not be met simultaneously, often interrelated between indices, so Electric Power Network Planning should be assessed on the whole, consider the factor of each side.Meanwhile, the evaluation scheme of proposition is the assessment carried out based on power supply reliability, so assessment result well can reflect the deficiency of electric network reliability aspect.And then can ensure assessment result be based on the basis of reliability on.

Further, the invention provides a kind of method calculating weight matrix according to evaluating matrix, specific as follows: to have r position electrical network assessment experts to assess the n of an electrical network index, and provide assessed value, obtain the evaluating matrix comprising all assessed values $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right],$ Wherein l _sjbe the assessed value that provide of s expert to a jth index.Receive predefined multiple white function for calculating the weight matrix of evaluating matrix, from multiple white function, select a predetermined white function as the function processed the assessed value of this index according to the value experience distribution of each index respectively, and obtain the weight matrix of evaluating matrix according to each element of selected white function process evaluating matrix.Use f ₁(x), f ₂(x) ... f _i(x) ... f _mx () represents each white function, be assumed to jth item choose targets i-th white function, just use f _is assessed value of (x) process jth item index, i.e. the jth row of matrix L.Then, according to formula n _sj=f _i(l _sj) calculate evaluating matrix Grey System counting n _sj, according to formula calculating comments total Grey System to count n _j.To be counted by the Grey System of evaluating matrix and total Grey System counting can calculate the weight matrix of evaluating matrix L $R=\left[\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ r_{r1}& r_{r2}& ...& r_{\mathrm{rn}}\end{array}\right],$ Wherein and the span of s, j is: s gets 1 to r successively, and j gets 1 to n successively.

Utilize gray system theory that the assessed value of assessment experts is carried out process and obtain weight matrix, Electric Power Network Planning is assessed again with weight matrix, the professional knowledge of expert and intelligence can be utilized on the one hand, assessment experts can be avoided the problem in the dysgnosia face of power distribution network on the other hand, improve the accuracy of assessment.And then improve the accuracy of electrical network assessment.

Further, the multiple white functions calculating the employing of each opinion rating comprise class morphic function, middle class morphic function and lower class morphic function, Fig. 2 a to Fig. 2 c is respectively the functional arrangement of class morphic function, middle class morphic function or lower class morphic function, wherein, to be upper its function expression of class morphic function be Fig. 2 a $f_1\left(x\right)=\left\{\begin{array}{cc}\frac{x}{l_1}& x\∈[0,l_1]\\ 1& x\∈[l_1,\∞)\\ 0& x\∈(-\∞,0)\end{array}\right.,$ Fig. 2 b is middle its function expression of class morphic function $f_2\left(x\right)=\left\{\begin{array}{cc}\frac{x}{l_1}& x\∈[0,l_1]\\ 2-\frac{x}{l_1}& x\∈[l_1,2l_1]\\ 0& x\∉\left(\mathrm{0,2}{l}_1\right]\end{array}\right.,$ Fig. 2 c is its function expression of lower class morphic function $f_3\left(x\right)=\left\{\begin{array}{cc}1& x\∈[0,l_1]\\ \frac{l_2-x}{l_2-l_1}& x\∈[l_1,l_2]\\ 0& x\∉(0,l_2]\end{array}\right..$ In Fig. 2 a to Fig. 2 c _l1 and l ₂value by each index span by according to formula n _sj=f _i(l _sj) calculate Grey System counting n _sjfixed.Time independent variable l _sjthe value experience distribution of corresponding jth item index determines.

When assessing electrical network, according to the actual conditions of Electric Power Network Planning, selecting rational white function, the validity of Grey System counting can be improved when recycling white function calculates Grey System counting, and then effectively can improve the validity of weight matrix.

Further, the method calculating the weight of each described index is specially: according to formula ${\mathrm{\ξ}}_j\left(s\right)=\frac{\underset{j}{\min }\underset{s}{\min }|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}{|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}$ Compute associations coefficient, wherein ξ _js () is the degree of association coefficient of a jth index, l _maxs=max{l _s1, l _s2..., l _sr, ρ is for presetting resolution coefficient, and usual ρ gets 0.5, but different systems is different.Calculate after correlation coefficient again according to formula compute associations degree, wherein r _jfor the degree of association of a jth index.

Comprehensive assessment expertise, development of judgment matrix also calculates the sequence α of each described index with AHM method meter _j, then according to the weight of following formulae discovery every index: wherein, w _jfor the weight of described jth item index.

Particularly, the tool method calculating the sequence of each index is:

First, according to piecewise function $a_{\mathrm{sj}}=\left\{\begin{array}{cc}0& l_{\mathrm{sj}}\∈\left(\mathrm{0,0.1}\right)\\ \frac{1}{\mathrm{int}(l_{\mathrm{sj}}\×10)}& l_{\mathrm{sj}}\∈\left[\mathrm{0.1,1}\right)\\ \mathrm{int}\left(l_{\mathrm{sj}}\right)& l_{\mathrm{sj}}\∈\left[\mathrm{1,10}\right)\\ 9& l_{\mathrm{sj}}\∈[10,+\∞)\end{array}\right.$ To matrix $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Each element carry out process and obtain judgment matrix $A=\left[\begin{array}{cccc}{a}_{11}& a_{12}& ...& a_{1n}\\ a_{21}& a_{22}& ...& a_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ a_{r1}& a_{r2}& ...& a_{\mathrm{rn}}\end{array}\right],$ Wherein, int is rounding operation.

Then, to each element piecewise function of judgment matrix A process, obtain matrix $\mathrm{\μ}=\left[\begin{array}{cccc}{\mathrm{\μ}}_{11}& {\mathrm{\μ}}_{12}& ...& {\mathrm{\μ}}_{1n}\\ {\mathrm{\μ}}_{21}& {\mathrm{\μ}}_{22}& ...& {\mathrm{\μ}}_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ {\mathrm{\μ}}_{r1}& {\mathrm{\μ}}_{r2}& ...& {\mathrm{\μ}}_{\mathrm{rn}}\end{array}\right].$

Finally, according to formula ${\mathrm{\α}}_j=\frac{2}{n(n-1)}\underset{i=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\μ}}_{\mathrm{ij}}$ Calculate sequence, wherein, $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_j=1.$

Take the grey correlation methods based on AHM to determine weight, the knowledge that effectively can play on the one hand expert, with intelligent, on the other hand, can avoid the deficiency that expert is familiar with distribution network planning reliability, thus the precision that raising assessment weight is determined.Further increase the accuracy of electrical network assessment.

Further, be B=WR according to the computing formula of the goal-based assessment value of each described index of weight calculation of described weight matrix and each described index.Wherein, W=(w ₁w ₂w _n), B is the set of the goal-based assessment value of each described index.

Describe as can be seen from volume above: provide multiple assessed value by each index in the multiple indexs to the assessment electrical network formulated, determine evaluating matrix, and the weight matrix of evaluating matrix is calculated according to evaluating matrix, calculate the weight of each index, and assess Electric Power Network Planning by the method for the assessed value of each evaluation index of weight matrix meter, obtain assessing the valuation of each quantification of targets in electricity planning.Multiple assessment factor or evaluation index are converted into the information incorporated that can reflect electrical network general status, solve the problem cannot assessing Electric Power Network Planning in prior art on the whole, thus can assessment Electric Power Network Planning on the whole, reach the effect of the directiveness improving Electric Power Network Planning assessment.

The appraisal procedure of the distribution network planning that the embodiment of the present invention provides, utilizes the method for gray theory to calculate judgment matrix, by definition white function, calculates relevant Grey System counting, effectively can improve the validity of judgment matrix.By the assessment of expert is combined with gray system theory, assessment experts effectively can be avoided not enough to the understanding of Electric Power Network Planning, the accuracy of assessment can be improved.

Further, after the goal-based assessment value of each the described index of weight calculation according to described weight matrix and each described index, described appraisal procedure also comprises: receive a predefined evaluation grade set V=(v ₁, v ₂..., v _m), adopt Delphi method to calculate each evaluation grade v _ipoint value of evaluation d _i, then according to formula Z=BD ^tcalculate the score value of described distribution network planning, wherein, D ^t=(d ₁d ₂d _m) ^t, Z is the point value of evaluation of described distribution network planning.By score value Z and the d of distribution network planning _icompare, d immediate with Z _icorresponding grade v _ifor the evaluation grade of power distribution network.

The embodiment of the present invention additionally provides the apparatus for evaluating of Electric Power Network Planning, this apparatus for evaluating is mainly used in the appraisal procedure performing the Electric Power Network Planning that embodiment of the present invention foregoing provides, and is specifically introduced below to the apparatus for evaluating of the Electric Power Network Planning that the embodiment of the present invention provides:

Fig. 3 is the schematic diagram of the apparatus for evaluating of Electric Power Network Planning according to the embodiment of the present invention, and as shown in Figure 3, this apparatus for evaluating mainly comprises receiving element 20, processing unit 40, the first computing unit 60, and the second computing unit 70.Particularly:

Receiving element 20, for receiving multiple initial assessment values of each index in distribution network planning many index, obtains the evaluating matrix of many index.Particularly, before assessment Electric Power Network Planning, first formulate the index of assessment Electric Power Network Planning, the assessment experts of multidigit Electric Power Network Planning provides assessed value respectively to each index, obtains evaluating matrix.The index of Electric Power Network Planning assessment comprises the index of the various aspects of Electric Power Network Planning, as reliability, economy, adaptability, harmony, user satisfaction etc.

Processing unit 40, for adopting predefined function process evaluating matrix, obtains the weight matrix of evaluating matrix.Particularly, each element adopting Grey Statistical method to calculate evaluating matrix belongs to the weights of each evaluation grade: first determine evaluation grade, the weight function of each evaluation grade is calculated again by predetermined white function, respectively with each element of the weight function process evaluating matrix of each grade, obtain the weights that each element of evaluating matrix belongs to each evaluation grade, then obtain the weight matrix of evaluating matrix according to the weights that evaluating matrix belongs to each evaluation grade.

First computing unit 60 is for calculating the weight of each index.Particularly, according to the suggestion development of judgment matrix of assessment experts, AHM method is utilized to calculate the relative order of evaluation index.Utilize evaluating matrix to calculate the correlation coefficient of each index, thus calculate the degree of association.The weight of each index is obtained again by the relative order of each index and calculation of relationship degree.

Second computing unit 70 is for the goal-based assessment value of each index of weight calculation according to weight matrix and each index.Particularly, the row matrix that the goal-based assessment value that the row matrix that forms of the weight of each index and the product of weight matrix are each evaluation index is formed.What this row matrix reflected is the score of each index in whole Electric Power Network Planning.

The apparatus for evaluating of the distribution network planning of the embodiment of the present invention, multiple assessed value is provided by each index in the multiple indexs to the assessment electrical network formulated, determine evaluating matrix, and the weight matrix of evaluating matrix is calculated according to evaluating matrix, calculate the weight of each index, and assess Electric Power Network Planning by the method for the assessed value of each evaluation index of weight matrix meter, obtain assessing the valuation of each quantification of targets in electricity planning.Multiple assessment factor or evaluation index are converted into the information incorporated that can reflect electrical network general status, solve the problem cannot assessing Electric Power Network Planning in prior art on the whole, thus can assessment Electric Power Network Planning on the whole, reach the effect of the directiveness improving Electric Power Network Planning assessment.

Fig. 4 is the schematic diagram of the apparatus for evaluating of Electric Power Network Planning according to the preferred embodiment of the invention, as shown in Figure 4:

Processing unit 40 mainly comprises chooser unit 402 and the first computation subunit unit 404, wherein:

Chooser unit 402 selects a predetermined white function as the function processed the assessed value of this index for the value distribution respectively according to each index from multiple white function.Wherein, multiple white function is the predefined white function received, and these white functions are for calculating the weight matrix of evaluating matrix.

First computation subunit 404 is for calculating the weight matrix of evaluating matrix, specific as follows: suppose have r position electrical network assessment experts to assess the n of an electrical network index, and provide assessed value, obtain the evaluating matrix comprising all assessed values $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right],$ Wherein l _sjbe the assessed value that provide of s expert to a jth index.Use f ₁(x), f ₂(x) ... f _i(x) ... f _mx () represents each white function, be assumed to jth item choose targets i-th white function, just use f _ix s assessed value of () process jth item index, i.e. the jth row of matrix L, then according to formula n _sj=f _i(l _sj) calculate evaluating matrix Grey System counting n _sj, and according to formula calculating comments total Grey System to count n _j.To be counted by the Grey System of evaluating matrix and total Grey System counting can calculate the weight matrix of evaluating matrix L $R=\left[\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ r_{r1}& r_{r2}& ...& r_{\mathrm{rn}}\end{array}\right],$ Wherein and the span of s, j, i is: s gets 1 to r successively, and j gets 1 to n successively.

Utilize gray system theory that the assessed value of assessment experts is carried out process and obtain weight matrix, Electric Power Network Planning is assessed again with weight matrix, the professional knowledge of expert and intelligence can be utilized on the one hand, assessment experts can be avoided the problem in the dysgnosia face of power distribution network on the other hand, improve the accuracy of assessment.And then improve the accuracy of electrical network assessment.

When assessing electrical network, according to the actual conditions of Electric Power Network Planning, selecting rational white function, the validity of Grey System counting can be improved when recycling white function calculates Grey System counting, and then effectively can improve the validity of weight matrix.

Further, the first computing unit 60 mainly comprises the second computation subunit 602, the 3rd computation subunit 604 and the 4th computation subunit 606, and wherein, the second computation subunit 602 is for according to following formulae discovery correlation coefficient:

${\mathrm{\ξ}}_j\left(s\right)=\frac{\underset{j}{\min }\underset{s}{\min }|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}{|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}$

Wherein l _maxs=max{l _s1, l _s2..., l _sr, ρ is for presetting resolution coefficient.

3rd computation subunit 604 is for calculating the sequence α of each described index _j, particularly, the 3rd computation subunit 604 comprises the first processing module 6041, second processing module 6042 and comparison module 6043.

First processing module 6041 is for according to piecewise function $a_{\mathrm{sj}}=\left\{\begin{array}{cc}0& l_{\mathrm{sj}}\∈\left(\mathrm{0,0.1}\right)\\ \frac{1}{\mathrm{int}(l_{\mathrm{sj}}\×10)}& l_{\mathrm{sj}}\∈\left[\mathrm{0.1,1}\right)\\ \mathrm{int}\left(l_{\mathrm{sj}}\right)& l_{\mathrm{sj}}\∈\left[\mathrm{1,10}\right)\\ 9& l_{\mathrm{sj}}\∈[10,+\∞)\end{array}\right.$ To matrix $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Each element carry out process and obtain judgment matrix $A=\left[\begin{array}{cccc}{a}_{11}& a_{12}& ...& a_{1n}\\ a_{21}& a_{22}& ...& a_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ a_{r1}& a_{r2}& ...& a_{\mathrm{rn}}\end{array}\right],$ Wherein, int is rounding operation.

Second processing module 6042 is for each the element piecewise function to judgment matrix A process, obtain matrix $\mathrm{\μ}=\left[\begin{array}{cccc}{\mathrm{\μ}}_{11}& {\mathrm{\μ}}_{12}& ...& {\mathrm{\μ}}_{1n}\\ {\mathrm{\μ}}_{21}& {\mathrm{\μ}}_{22}& ...& {\mathrm{\μ}}_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ {\mathrm{\μ}}_{r1}& {\mathrm{\μ}}_{r2}& ...& {\mathrm{\μ}}_{\mathrm{rn}}\end{array}\right];$

Comparison module 6043 is for according to formula ${\mathrm{\α}}_j=\frac{2}{n(n-1)}\underset{i=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\μ}}_{\mathrm{ij}}$ Calculate sequence, wherein, $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_j=1.$

4th computation subunit 606 is for calculating the weight of every index as follows:

$w_j=\frac{\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)}{\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)\right)}$

Wherein, w _jfor the weight of described jth item index.

Take the grey correlation methods based on AHM to determine weight, the knowledge that effectively can play on the one hand expert, with intelligent, on the other hand, can avoid the deficiency that expert is familiar with distribution network planning reliability, thus the precision that raising assessment weight is determined.Further increase the accuracy of electrical network assessment.

Further, second calculates Unit 70 comprises the 5th computation subunit the 702, five computation subunit 702 for calculating the goal-based assessment value of each described index according to formula B=WR, wherein, and W=(w ₁w ₂w _n), B is the set of the goal-based assessment value of each described index.

As can be seen from the above description, the apparatus for evaluating of the distribution network planning of the embodiment of the present invention, when Electric Power Network Planning is assessed, weight matrix is obtained with Grey Statistical method process evaluating matrix, given full play to the professional knowledge knowledge of electrical network assessment experts in electrical network assessment, avoid assessment experts assessment result that is that cause is inaccurate to electrical network understanding is not enough simultaneously.Adopt the grey relational grade based on AHM method to determine the weight of each index, improve the precision of agriculture products weight.The accuracy of further raising electrical network assessment.

Further preferably, the electrical network apparatus for evaluating that the embodiment of the present invention provides also comprises the second receiving element 50, the 3rd computing unit 80, the 4th computing unit 90 and comparing unit 100, second receiving element 50 is for receiving evaluation grade set (namely first presetting set), and the 3rd computing unit 80 presets element v in set for adopting Delphi method to calculate described first _ipoint value of evaluation d _j; 4th computing unit 90 is for according to formula Z=BD ^tcalculate the score value of described distribution network planning, wherein, D ^t=(d ₁, d ₂..., d _m) ^t, Z is the point value of evaluation of described distribution network planning; Comparing unit 100, for the score value of distribution network planning and evaluation grade set being compared, obtains the evaluation grade of distribution network planning.

By to evaluation grade assignment, clearly can represent the evaluation grade of the index that electrical network is assessed and the contrast with other indexs, the point value of evaluation of Electric Power Network Planning can judge the opinion rating residing for Electric Power Network Planning, and can be used to compare with other Electric Power Network Planning.Meanwhile, by the grade of the score determination Electric Power Network Planning to Electric Power Network Planning, make assessment result more vivid.

Obviously, those skilled in the art should be understood that, above-mentioned of the present invention each module or each step can realize with general calculation element, they can concentrate on single calculation element, or be distributed on network that multiple calculation element forms, alternatively, they can realize with the executable program code of calculation element, thus, they can be stored and be performed by calculation element in the storage device, or they are made into each integrated circuit modules respectively, or the multiple module in them or step are made into single integrated circuit module to realize.Like this, the present invention is not restricted to any specific hardware and software combination.

The foregoing is only the preferred embodiments of the present invention, be not limited to the present invention, for a person skilled in the art, the present invention can have various modifications and variations.Within the spirit and principles in the present invention all, any amendment done, equivalent replacement, improvement etc., all should be included within protection scope of the present invention.

Claims (13)

1. an appraisal procedure for distribution network planning, is characterized in that, comprising:

Receive multiple initial assessment values of each described index in described distribution network planning many index, obtain the evaluating matrix of multinomial described index;

Adopt evaluating matrix described in predefined function process, obtain the weight matrix of described evaluating matrix;

Calculate the weight of each described index; And

According to the goal-based assessment value of each described index of weight calculation of described weight matrix and each described index.

2. appraisal procedure according to claim 1, is characterized in that, described predefined function comprises multiple predetermined white function, and adopt evaluating matrix described in pre-defined function process, the weight matrix obtaining described evaluating matrix comprises:

The described predetermined white function of each described choose targets one is respectively, wherein, for the described predetermined white function of different described choose targets is identical or different from multiple described white function; And

According to evaluating matrix described in following formulae discovery $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Weight matrix $R=\left[\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ r_{r1}& r_{r2}& ...& r_{\mathrm{rn}}\end{array}\right]:$

$r_{\mathrm{sj}}=\frac{f_i\left(l_{\mathrm{sj}}\right)}{\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{f}_i\left(l_{\mathrm{sj}}\right)},$

Wherein, l _sjfor s assessed value of jth item index in multinomial described index, f _i(l _sj) be function f _ix in (), independent variable x value is l _sjtime corresponding functional value, f _ix () is the described predetermined white function of described jth item choose targets, r _sjfor s weights of described jth item index, and m, n and r are the natural number of more than 2, and s gets 1 to r successively, and j gets 1 to n successively.

3. appraisal procedure according to claim 2, is characterized in that, the weight calculating each described index comprises:

According to formula ${\mathrm{\ξ}}_j\left(s\right)=\frac{\underset{j}{\min }\underset{s}{\min }|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}{|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}$ Compute associations coefficient, wherein l _maxs=max{l _s1, l _s2..., l _sr, ρ is for presetting resolution coefficient;

Calculate the sequence α of each described index _j; And

According to formula $w_j=\frac{\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)}{\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)\right)}$ Calculate the weight of each described index, wherein, w _jfor the weight of described jth item index.

4. appraisal procedure according to claim 3, is characterized in that, calculates the sequence α of each described index _jcomprise:

According to piecewise function $a_{\mathrm{sj}}=\left\{\begin{array}{cc}0& l_{\mathrm{sj}}\∈\left(\mathrm{0,0.1}\right)\\ \frac{1}{\mathrm{int}(l_{\mathrm{sj}}\×10)}& l_{\mathrm{sj}}\∈\left[\mathrm{0.1,1}\right)\\ \mathrm{int}\left(l_{\mathrm{sj}}\right)& l_{\mathrm{sj}}\∈\left[\mathrm{1,10}\right)\\ 9& l_{\mathrm{sj}}\∈[10,+\∞)\end{array}\right.$ To matrix $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Each element carry out process and obtain matrix $A=\left[\begin{array}{cccc}{a}_{11}& a_{12}& ...& a_{1n}\\ a_{21}& a_{22}& ...& a_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ a_{r1}& a_{r2}& ...& a_{\mathrm{rn}}\end{array}\right];$

To each element piecewise function of matrix A process, obtain matrix $\mathrm{\μ}=\left[\begin{array}{cccc}{\mathrm{\μ}}_{11}& {\mathrm{\μ}}_{12}& ...& {\mathrm{\μ}}_{1n}\\ {\mathrm{\μ}}_{21}& {\mathrm{\μ}}_{22}& ...& {\mathrm{\μ}}_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ {\mathrm{\μ}}_{r1}& {\mathrm{\μ}}_{r2}& ...& {\mathrm{\μ}}_{\mathrm{rn}}\end{array}\right];$ And

According to formula calculate sequence, wherein, int is rounding operation,

5. appraisal procedure according to claim 3, is characterized in that, the goal-based assessment value according to each described index of weight calculation of described weight matrix and each described index comprises:

The goal-based assessment value of each described index is calculated according to formula B=WR, wherein, W=(w ₁w ₂w _n), B is the set of the goal-based assessment value of each described index.

6. appraisal procedure according to claim 5, is characterized in that, after the goal-based assessment value of each the described index of weight calculation according to described weight matrix and each described index, described appraisal procedure also comprises:

Receive first and preset set V=(v ₁, v ₂..., v _m);

Calculate described first and preset element v in set _ipoint value of evaluation d _i;

According to formula Z=BD ^tcalculate the score value of described distribution network planning, wherein, D ^t=(d ₁d ₂d _m) ^t, Z is the point value of evaluation of described distribution network planning; And

The score value of more described distribution network planning and described first is preset and is gathered, and draws the evaluation grade of described distribution network planning.

7. appraisal procedure according to claim 2, is characterized in that, multiple described predetermined white function comprises: upper class morphic function, middle class morphic function and lower class morphic function, wherein,

The function expression of described upper class morphic function is $f_1\left(x\right)=\left\{\begin{array}{cc}\frac{x}{l_1}& x\∈[0,l_1]\\ 1& x\∈[l_1,\∞)\\ 0& x\∈(-\∞,0)\end{array}\right.,$

The function expression of described middle class morphic function is $f_2\left(x\right)=\left\{\begin{array}{cc}\frac{x}{l_1}& x\∈[0,l_1]\\ 2-\frac{x}{l_1}& x\∈[l_1,2l_1]\\ 0& x\∉\left(\mathrm{0,2}{l}_1\right]\end{array}\right.,$

The function expression of described lower class morphic function is $f_3\left(x\right)=\left\{\begin{array}{cc}1& x\∈[0,l_1]\\ \frac{l_2-x}{l_2-l_1}& x\∈[l_1,l_2]\\ 0& x\∉(0,l_2]\end{array}\right.,$

Wherein, l ₁and l ₂value be preset value.

8. an apparatus for evaluating for distribution network planning, is characterized in that, comprising:

First receiving element, for receiving multiple initial assessment values of each described index in described distribution network planning many index, obtains the evaluating matrix of multinomial described index;

Processing unit, for adopting evaluating matrix described in predefined function process, obtains the weight matrix of described evaluating matrix;

First computing unit, for calculating the weight of each described index; And

Second computing unit, for the goal-based assessment value of each the described index of weight calculation according to described weight matrix and each described index.

9. apparatus for evaluating according to claim 8, is characterized in that, described predefined function comprises multiple predetermined white function, and described processing unit comprises:

Chooser unit, is respectively the described predetermined white function of each described choose targets one from multiple described white function, wherein, for the described predetermined white function of different described choose targets is identical or different; And

First computation subunit: for according to evaluating matrix described in following formulae discovery $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Weight matrix $R=\left[\begin{array}{cccc}{r}_{11}& r_{12}& ...& r_{1n}\\ r_{21}& r_{22}& ...& r_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ r_{r1}& r_{r2}& ...& r_{\mathrm{rn}}\end{array}\right]:$

$r_{\mathrm{sj}}=\frac{f_i\left(l_{\mathrm{sj}}\right)}{\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{f}_i\left(l_{\mathrm{sj}}\right)},$

Wherein, l _sjfor s assessed value of jth item index in multinomial described index, f _i(l _sj) be function f _ix in (), independent variable x value is l _sjtime corresponding functional value, f _ix () is the described predetermined white function of described jth item choose targets, r _sjfor s weights of described jth item index, and m, n and r are the natural number of more than 2, and s gets 1 to r successively, and j gets 1 to n successively.

10. apparatus for evaluating according to claim 9, is characterized in that, described first computing unit comprises:

Second computation subunit, for according to formula ${\mathrm{\ξ}}_j\left(s\right)=\frac{\underset{j}{\min }\underset{s}{\min }|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}{|l_{\max s}-l_{\mathrm{js}}|+\mathrm{\ρ}\underset{j}{\max }\underset{s}{\max }|l_{\max s}-l_{\mathrm{js}}|}$ Compute associations coefficient, wherein l _maxs=max{l _s1, l _s2..., l _sr, ρ is for presetting resolution coefficient;

3rd computation subunit, for calculating the sequence α of each described index _j; And

4th computation subunit, for according to formula $w_j=\frac{\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)}{\underset{j=1}{\overset{n}{\mathrm{\Σ}}}\left(\frac{{\mathrm{\α}}_j}{r}\underset{s=1}{\overset{r}{\mathrm{\Σ}}}{\mathrm{\ξ}}_j\left(s\right)\right)}$ Calculate the weight of each described index, wherein, w _jfor the weight of described jth item index.

11. apparatus for evaluating according to claim 10, is characterized in that, described 3rd computation subunit comprises:

First processing module, for according to piecewise function $a_{\mathrm{sj}}=\left\{\begin{array}{cc}0& l_{\mathrm{sj}}\∈\left(\mathrm{0,0.1}\right)\\ \frac{1}{\mathrm{int}(l_{\mathrm{sj}}\×10)}& l_{\mathrm{sj}}\∈\left[\mathrm{0.1,1}\right)\\ \mathrm{int}\left(l_{\mathrm{sj}}\right)& l_{\mathrm{sj}}\∈\left[\mathrm{1,10}\right)\\ 9& l_{\mathrm{sj}}\∈[10,+\∞)\end{array}\right.$ To matrix $L=\left[\begin{array}{cccc}{l}_{11}& l_{12}& ...& l_{1n}\\ l_{21}& l_{22}& ...& l_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ l_{r1}& l_{r2}& ...& l_{\mathrm{rn}}\end{array}\right]$ Each element carry out process and obtain matrix $A=\left[\begin{array}{cccc}{a}_{11}& a_{12}& ...& a_{1n}\\ a_{21}& a_{22}& ...& a_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ a_{r1}& a_{r2}& ...& a_{\mathrm{rn}}\end{array}\right];$

Second processing module, for piecewise function each element of matrix A is processed, obtains matrix $\mathrm{\μ}=\left[\begin{array}{cccc}{\mathrm{\μ}}_{11}& {\mathrm{\μ}}_{12}& ...& {\mathrm{\μ}}_{1n}\\ {\mathrm{\μ}}_{21}& {\mathrm{\μ}}_{22}& ...& {\mathrm{\μ}}_{2n}\\ .& .& .& .\\ .& .& .& .\\ .& .& .& .\\ {\mathrm{\μ}}_{r1}& {\mathrm{\μ}}_{r2}& ...& {\mathrm{\μ}}_{\mathrm{rn}}\end{array}\right];$ And

Computing module, for according to formula calculate sequence, wherein, int is rounding operation, $\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{\mathrm{\α}}_j=1.$

12. apparatus for evaluating according to claim 10, is characterized in that, described second computing unit comprises:

5th computation subunit, for calculating the goal-based assessment value of each described index according to formula B=WR, wherein, W=(w ₁w ₂w _n), B is the set of the goal-based assessment value of each described index.

13. apparatus for evaluating according to claim 12, is characterized in that, described apparatus for evaluating also comprises:

Second receiving element, presets set for receiving first;

3rd computing unit, presets element v in set for calculating described first _ipoint value of evaluation d _j;

4th computing unit, for according to formula Z=BD ^tcalculate the score value of described distribution network planning, wherein, D ^t=(d ₁, d ₂..., d _m) ^t, Z is the point value of evaluation of described distribution network planning; And

Comparing unit, the score value and described first for more described distribution network planning is preset and is gathered, and draws the evaluation grade of described distribution network planning.