CN103678943A - Multi-index fuzzy evaluation method for grid faults caused by disasters - Google Patents

Abstract

The invention belongs to the technical field of electrical power system risk evaluation, and particularly relates to a multi-index fuzzy evaluation method for grid faults caused by disasters. The evaluation method comprises the following steps of providing four indexes for evaluating a grid affected by the disasters according to an operational aspect of an electric transmission line; fuzzifying the indexes by utilizing a fuzzy mathematic theory; respectively carrying out weight analysis on the evaluated indexes through an analytic hierarchy process and an entropy evaluation method to obtain a primary weight and a secondary weight of each evaluated index; and synthesizing the weights obtained by the two methods, and combining a method of weighted mean obtain a comprehensive evaluation result of the grid faults caused by the disasters, and form a fuzzy synthetic evaluation method. The evaluation method takes multiple influence factors of natural disasters on the grid into account, can be used for carrying out comprehensive comparison and analysis on influence of various natural disasters on the grid, and has stronger comprehensive and objectivity.

Description

A kind of disaster causes many index Fuzzies decision method of electric network fault

Technical field

The invention belongs to electric system risk decision technology field, be specifically related to many index Fuzzies decision method that a kind of disaster causes electric network fault.

Background technology

In recent years, global extreme climate variation causes Disaster Event showed increased, and the frequent difficulty of controlling power network safety operation that increased of Disaster Event, also has higher requirement to electrical network reliable power supply.China's disaster has diversity, frequency and zonal feature, in order to strengthen the ability of electrical network reply catastrophe, sets up disaster alarm mechanism, should the influence degree of electrical network be studied targetedly and be deployed troops on garrison duty according to disaster.

At present, disaster mainly concentrates on the statistics and analysis of disaster to electric network influencing result to the research of effect on power system.In concrete analysis disaster, cause in the process of electric network fault, its analysis indexes only relies on disaster effect number of times to evaluate explanation, does not consider the situations such as transmission line of electricity electric pressure, transmission line length and automatic reclosing, has larger defective.

Therefore, how when analyzing affecting that disaster caused electrical network, consider that a plurality of indexs comprehensively analyze, reflect the capability of influence of disaster to electrical network comprehensively, significant for the ability of strengthening electrical network reply catastrophe.

Summary of the invention

The present invention is directed to the deficiencies in the prior art, proposed many index Fuzzies decision method that a kind of disaster causes electric network fault.

This decision method has proposed 4 according to the ruuning situation of transmission line of electricity and has judged that disaster affects the index of electrical network, utilize fuzzy mathematics theory by its obfuscation, and respectively judgement index is carried out to weight analysis by analytical hierarchy process and Information Entropy, and the weight that two kinds of methods are tried to achieve is carried out comprehensively, in conjunction with method of weighted mean, formed fuzzy synthetic appraisement method.Finally, according to real data, carry out sample calculation analysis, comparative analysis can count the ability to function of disaster to electric system.

A kind of disaster of the present invention causes many index Fuzzies decision method of electric network fault, comprises the following steps:

A kind of disaster causes many index Fuzzies decision method of electric network fault, it is characterized in that, based on 4 kinds of disasters of definition, affect the judgement index of electrical network ability: tripping operation number of times, unplanned stoppage in transit number of times, region power transmission line comprehensive trip-out rate and reclosing failure rate, specifically comprise the following steps:

Step 1, the degree of membership based on fuzzy mathematics is theoretical, by described 4 kinds of judgement index Fuzzies, obtains normalized fuzzy overall evaluation matrix R;

Step 2, based on analytical hierarchy process, determines above-mentioned 4 main weights W of judging index;

Step 3, based on Information Entropy, determines the inferior weight V that respectively judges index according to 4 of obfuscation indexs;

Step 4, the inferior weight V that the main weights W obtaining based on step 2 and step 3 obtain, obtains the comprehensive weight vector C that judges index;

Step 5, based on method of weighted mean, the fuzzy overall evaluation matrix R obtaining according to step 1 and judgement index comprehensive weight vector C determine comprehensive evaluation result vector B.

In above-mentioned a kind of disaster, cause many index Fuzzies decision method of electric network fault, described tripping operation number of times NT(j) represent, specifically refer to the number of times that disaster j causes electrical network tripping operation every year, its unit is next year;

Described unplanned stoppage in transit number of times N _nPO(j) represent, specifically refer to the number of times that disaster j causes electrical network tripping operation every year, its unit is next year;

Described region power transmission line comprehensive trip-out rate R _cT(j) represent, based on following formula:

$R_{\mathrm{CT}}\left(j\right)=\underset{i=1}{\overset{k}{\mathrm{\Σ}}}{\mathrm{\α}}_i{R}_{\mathrm{Ti}}\left(j\right)$

Wherein: α _ifor the weight of this electric pressure circuit, this coefficient is relevant with economic transmission capacity and the fed distance of transmission line of electricity; R _cT(j) be the trip-out rate of this electric pressure transmission line of electricity, unit is inferior/100 km years; R _cT(j) be region power transmission line comprehensive trip-out rate, unit is inferior/100 km years;

Wherein, trip-out rate is characterized by:

$R_{\mathrm{Ti}}\left(j\right)=\frac{N_{\mathrm{Ti}}\left(j\right)}{L}$

Wherein: L is the length of specific voltage grade transmission line of electricity, unit was 100 km years, R _ti(j) be the trip-out rate of this electric pressure transmission line of electricity, unit is inferior/100 km years, N _ti(j) be the tripping operation number of times of this electric pressure transmission line of electricity;

Described reclosing failure rate R _rF(j) represent, based on following formula:

$R_{\mathrm{RF}}\left(j\right)=\frac{N_{\mathrm{NPO}}\left(j\right)}{N_T}\×100\%$

Wherein, R _rF(j) the Closing fault rate of attaching most importance to, dimensionless; N _t(j) be tripping operation number of times; N _nPO(j) be the number of times of the unplanned stoppage in transit of transmission facility.

In above-mentioned a kind of disaster, cause many index Fuzzies decision method of electric network fault, described 4 kinds of obfuscations of judging indexs are based on following formula:

${x_{\mathrm{ij}}}^s=\frac{x_{\mathrm{ij}}}{\underset{j\∈I}{\max }\left\{x_{\mathrm{ij}}\right\}+\underset{j\∈I}{\min }\left\{x_{\mathrm{ij}}\right\}}$

Wherein: for x _ij, i=1,2,3,4; J=1,2 ..., k, represents that i judgement of j kind disaster refers to target value, for x _ij ^s, i=1,2,3,4; J=1,2 ..., k, i the relative degree of membership value of judging index of expression j kind disaster, I represents disaster set to be evaluated;

Wherein: x _ijwith the above-mentioned 4 kinds relations of judging indexs, based on following formula:

x _1j=N _T（j）;

Wherein: N _t(j) be tripping operation number of times;

x _2j=N _NPO（j）;

Wherein: N _nPO(j) be the number of times of the unplanned stoppage in transit of transmission facility;

x _3j=R _CT（j）;

Wherein: R _cT(j) be region power transmission line comprehensive trip-out rate;

x _4j=R _RF（j）;

Wherein: R _rF(j) the Closing fault rate of attaching most importance to.

In above-mentioned a kind of disaster, cause many index Fuzzies decision method of electric network fault, the determining of normalized fuzzy overall evaluation matrix R in described step 1, based on following formula:

$r_{\mathrm{ij}}=\frac{{x_{\mathrm{ij}}}^s}{\underset{t=1}{\overset{j}{\mathrm{\Σ}}}{x_{\mathrm{it}}}^s}.$

In above-mentioned a kind of disaster, cause many index Fuzzies decision method of electric network fault, determining of the main weights W of judgement index based on analytical hierarchy process in described step 2, comprises the following steps:

Step 2.1, determine the quantitative criteria of index:

Main weights W by index i with respect to index j _ijby 1～9 scale, carry out quantification treatment, based on following formula:

w _ij=N

Wherein: w _ijfor the weight of index i with respect to index j, N is the integer in 1～9 scope;

Index j is with respect to the main weights W of index i _ji, based on following formula:

w _ji=1/w _ij

Step 2.2, determine initial flexible strategy:

According to above-mentioned formula, determine each factor x _i(i=1 ..., weight k), by the weight normalizing proposing, obtains weighted value and is w wherein _virepresent that v estimates i the weight of judging index, w _vi' represent the respective weights estimated value after normalizing; Finally, calculate the mean value of the weight estimated value proposing

and as the weight of every judgement index;

Step 2.3, the determining of weight:

First, the weight of asking for according to above-mentioned steps is set up judgment matrix W, the element w that in W, i is capable and j is listed as _ijrepresent to judge index w _iand w _jthe scaling ratio of gained relatively; Secondly, the geometric mean of every each calibration data of a line in compute matrix W, finally, be normalized, utilize w _i'=W _i∑ W _i, determine and respectively judge the weight that index is final, form weight vector W'=[w ₁', w ₂' ... w _n'], wherein n represents to judge the number of index.

In above-mentioned a kind of disaster, cause many index Fuzzies decision method of electric network fault, in described step 3, time weight V of the evaluation index based on Information Entropy determines, comprises the following steps:

Step 3.1, raw data matrix normalization:

If raw data matrix is A=(a _ij) _{k * n}, wherein k is for to judge that index n is as evaluation object; Judge that index is all that large person is excellent type, obtains normalization matrix based on following formula for 4:

$u_{\mathrm{ij}}=\frac{a_{\mathrm{ij}}}{\underset{1\&le;j\&le;n}{\max }\left\{a_{\mathrm{ij}}\right\}+\underset{1\&le;j\&le;n}{\mathrm{<figure-callout\; id="1"\; label="min"\; filenames="1312271750031.png"\; state="\{\{state\}\}">min</figure-callout>}}\left\{a_{\mathrm{ij}}\right\}}$

Step 3.2, the determining of entropy:

The entropy of i index is based on following formula:

$e_i=-\frac{\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{f}_{\mathrm{ij}}1\mathrm{<figure-callout\; id="1"\; label="n\; f\; ij"\; filenames="1312271750031.png"\; state="\{\{state\}\}">n</figure-callout>}{f}_{\mathrm{ij}}{}_{}}{1\mathrm{nn}}$

Wherein: $f_{\mathrm{ij}}=u_{\mathrm{ij}}/\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{u}_{\mathrm{ij}};$

Step 3.3, the determining of weight:

After having determined the entropy of i index, the determining based on following formula of i index weights:

$v_i=\frac{1-e_i}{k-\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{e}_i}(0\&le;v_i\&le;1,\underset{1}{\overset{k}{\mathrm{\&Sigma;}}}{v}_i=1)$

In above-mentioned a kind of disaster, cause many index Fuzzies decision method of electric network fault, the comprehensive weight vector C of described judgement index determines based on following formula:

$c_i=w_i^{`}{v}_i/\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{w}_i^{`}{v}_i(i=\mathrm{1,2},....k)$

Wherein: w _iand v _ithe every judgement index weights that is respectively analytical hierarchy process and Information Entropy calculating gained, comprehensive weight vector is C=(c _i, c ₂c _k).

In above-mentioned a kind of disaster, cause many index Fuzzies decision method of electric network fault, the determining based on following formula of the described comprehensive evaluation result vector based on method of weighted mean:

B=C·R

Wherein: B is comprehensive evaluation result vector, C is comprehensive weight vector, and R is fuzzy overall evaluation matrix.

Therefore, tool of the present invention has the following advantages: 1. 4 judgement indexs that the present invention proposes have not only been considered the number of times of disaster initiating system tripping operation, also consider the situation of transmission line of electricity electric pressure, transmission line length and automatic reclosing, comprehensively analyzed the influence factor of disaster to electrical network; 2. decision method proposed by the invention can be considered the impact of various disasteies on electrical network, has comprehensive and versatility; 3. decision method provided by the invention combines multiple structure power method and method of weighted mean, has both considered the suggestion of experts' evaluation, has considered again the objective impact of disaster, can objectively reflect the capability of influence of disaster to electrical network comprehensively.

Accompanying drawing explanation

Fig. 1 is process flow diagram of the present invention.

Fig. 2 is the capability of influence comparison diagrams of the different disasters that obtain of the present invention to electrical network.

Embodiment

Be the preferred embodiments of the present invention below, and by reference to the accompanying drawings, concrete application of the present invention be described further.

Embodiment:

One, first, introduce the Method And Principle the present invention relates to:

The present invention affects the judgement index of electrical network ability based on 4 kinds of disasters of definition: tripping operation number of times, unplanned stoppage in transit number of times, region power transmission line comprehensive trip-out rate and reclosing failure rate, wherein,

1. number of times N trips _t(j) represent, specifically refer to the number of times that disaster j causes electrical network tripping operation every year, its unit is next year;

2. unplanned stoppage in transit number of times N _nPO(j) represent, specifically refer to the number of times that disaster j causes electrical network tripping operation every year, its unit is next year;

3. region power transmission line comprehensive trip-out rate R _cT(j) represent, based on following formula:

$R_{\mathrm{CT}}\left(j\right)=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{\mathrm{\&alpha;}}_i{R}_{\mathrm{Ti}}\left(j\right)$

Wherein: α _ifor the weight of this electric pressure circuit, this coefficient is relevant with economic transmission capacity and the fed distance of transmission line of electricity; R _cT(j) be the trip-out rate of this electric pressure transmission line of electricity, unit is inferior/100 km years; R _cT(j) be region power transmission line comprehensive trip-out rate, unit is inferior/100 km years;

Wherein, trip-out rate is characterized by:

$R_{\mathrm{Ti}}\left(j\right)=\frac{N_{\mathrm{Ti}}\left(j\right)}{L}$

Wherein: L is the length of specific voltage grade transmission line of electricity, unit was 100 km years, R _ti(j) be the trip-out rate of this electric pressure transmission line of electricity, unit is inferior/100 km years, N _ti(j) be the tripping operation number of times of this electric pressure transmission line of electricity;

4. reclosing failure rate R _rF(j) represent, based on following formula:

$R_{\mathrm{RF}}\left(j\right)=\frac{N_{\mathrm{NPO}}\left(j\right)}{N_T}\&times;100\%$

Wherein, R _rF(j) the Closing fault rate of attaching most importance to, dimensionless; N _t(j) be tripping operation number of times; N _nPO(j) be the number of times of the unplanned stoppage in transit of transmission facility.

Specifically comprise the following steps:

(1) step 1, the degree of membership based on fuzzy mathematics is theoretical, by described 4 kinds of judgement index Fuzzies, obtains normalized fuzzy overall evaluation matrix R; Based on following formula:

$r_{\mathrm{ij}}=\frac{{x_{\mathrm{ij}}}^s}{\underset{t=1}{\overset{j}{\mathrm{\&Sigma;}}}{x_{\mathrm{it}}}^s}.$

4 kinds of obfuscations of judging indexs are based on following formula:

${x_{\mathrm{ij}}}^s=\frac{x_{\mathrm{ij}}}{\underset{j\&Element;I}{\max }\left\{x_{\mathrm{ij}}\right\}+\underset{j\&Element;I}{\min }\left\{x_{\mathrm{ij}}\right\}}$

Wherein: for x _ij, i=1,2,3,4; J=1,2 ..., k, represents that i judgement of j kind disaster refers to target value, for x _ij ^s, i=1,2,3,4; J=1,2 ..., k, i the relative degree of membership value of judging index of expression j kind disaster, I represents disaster set to be evaluated;

Wherein: x _ijwith the above-mentioned 4 kinds relations of judging indexs, based on following formula:

x _1j=N _T（j）;

Wherein: N _t(j) be tripping operation number of times;

x _2j=N _NPO（j）;

Wherein: N _nPO(j) be the number of times of the unplanned stoppage in transit of transmission facility;

x _3j=R _CT（j）;

Wherein: R _cT(j) be region power transmission line comprehensive trip-out rate;

x _4j=R _RF（j）;

Wherein: R _rF(j) the Closing fault rate of attaching most importance to.

(2) step 2, based on analytical hierarchy process, determines above-mentioned 4 main weights W of judging index; Specifically comprise the following steps:

Step 2.1, determine the quantitative criteria of index:

Main weights W by index i with respect to index j _ijby 1～9 scale, carry out quantification treatment, based on following formula:

w _ij=N

Wherein: w _ijfor the weight of index i with respect to index j, N is the integer in 1～9 scope; The value of N determines or random value according to the 1-9 ratio scaling law in AHP method, and 1-9 ratio scaling law is proposed by American scholar T professor .L.Saaty.

Index j is with respect to the main weights W of index i _ji, based on following formula:

w _ji=1/w _ij

Step 2.2, determine initial flexible strategy:

According to above-mentioned formula, determine each factor x _i(i=1 ..., weight k), by the weight normalizing proposing, obtains weighted value and is

w wherein _virepresent that v estimates i the weight of judging index, w _vi' represent the respective weights estimated value after normalizing; Finally, calculate the mean value of the weight estimated value proposing

and as the weight of every judgement index;

Step 2.3, the determining of weight:

First, the weight of asking for according to above-mentioned steps is set up judgment matrix W, the element w that in W, i is capable and j is listed as _ijrepresent to judge index w _iand w _jthe scaling ratio of gained relatively; Secondly, the geometric mean of every each calibration data of a line in compute matrix W,

finally, be normalized, utilize w _i'=W _i/ ∑ W _i, determine and respectively judge the weight that index is final, form weight vector W'=[w ₁', w ₂' ... w _n'], wherein n represents to judge the number of index.

(3) step 3, based on Information Entropy, determines the inferior weight V that respectively judges index according to 4 of obfuscation indexs; Comprise the following steps:

Step 3.1, raw data matrix normalization:

If raw data matrix is A=(a _ij) _{k * n}, wherein k is for to judge that index n is as evaluation object; Judge that index is all that large person is excellent type, obtains normalization matrix based on following formula for 4:

$u_{\mathrm{ij}}=\frac{a_{\mathrm{<figure-callout\; id="1"\; label="ij\; max"\; filenames="1312271750031.png"\; state="\{\{state\}\}">ij</figure-callout>}}}{\underset{}{\max }}$

Step 3.2, the determining of entropy:

The entropy of i index is based on following formula:

$e_i=-\frac{\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{f}_{\mathrm{ij}}1\mathrm{<figure-callout\; id="1"\; label="n\; f\; ij"\; filenames="1312271750031.png"\; state="\{\{state\}\}">n</figure-callout>}{f}_{\mathrm{ij}}{}_{}}{1\mathrm{nn}}$

Wherein: $f_{\mathrm{ij}}=u_{\mathrm{ij}}/\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{u}_{\mathrm{ij}};$

Step 3.3, the determining of weight:

After having determined the entropy of i index, the determining based on following formula of i index weights:

$v_i=\frac{1-e_i}{k-\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{e}_i}(0\&le;v_i\&le;1,\underset{1}{\overset{k}{\mathrm{\&Sigma;}}}{v}_i=1)$

(4) step 4, the inferior weight V that the main weights W obtaining based on step 2 and step 3 obtain, obtains the comprehensive weight vector C that judges index; Based on following formula:

$c_i=w_i^{`}{v}_i/\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{w}_i^{`}{v}_i(i=\mathrm{1,2},....k)$

Wherein: w _iand v _ithe every judgement index weights that is respectively analytical hierarchy process and Information Entropy calculating gained, comprehensive weight vector is C=(c _i, c ₂c _k).

(5) step 5, based on method of weighted mean, the fuzzy overall evaluation matrix R obtaining according to step 1 and judge that index comprehensive weight vector C determines comprehensive evaluation result vector B, based on following formula:

B=C·R

Wherein: B is comprehensive evaluation result vector, C is comprehensive weight vector, and R is fuzzy overall evaluation matrix.

Two, be a concrete case that adopts said method below:

According to 2009 to 2011 circuit operational reports of national grid, arrange out and comprise that thunder and lightning, icing, bird pest, strong wind, filth and six kinds of disaster related datas of mountain fire, region have covered all regions that China economizes except Guangdong, Guangxi, Guizhou, Yunnan and Hai Nanwu.With reference to larger 4 kinds of the alternating current circuits electric pressure of transmission line capability, and calculate weighted value according to their maximum delivery capacity and maximum delivery distance, as shown in table 2, and calculate according to this region power transmission line comprehensive trip-out rate.Within 2009～2011 years, six kinds of disasters are large to China

The judgement desired value that some areas impact is as shown in table 3.

Each grade transmission line of electricity weight reference table of table 2

2009～2011 years six kinds of China most areas disasters of table 3 are judged desired value

1) according to the step of comprehensive evaluation, want to judge desired value obfuscation by 4 of six kinds of disasters, the data obtained is in Table 4.

Table 4 is judged the obfuscation matrix of index

2), first according to analytical hierarchy process, with reference to evaluation expert's suggestion, try to achieve subjective weight as follows:

W'=(0.224211,0.259772,0.265448,0.250569)

Then according to Information Entropy, with reference to the raw data of judging index shown in table 3, try to achieve objective weight as follows:

V=(0.222845,0.256302,0.255035,0.265817)

Finally, according to formula (11), obtain comprehensive weight as follows:

C=(0.199181,0.26542,0.269878,0.265521)

3) draw and evaluate disaster to affect the comprehensive evaluation vector of electrical network ability as follows:

B=(0.723581,0.566729,0.177154,0.386284,0.109377,0.355372)

According to comprehensive evaluation vector, show that six kinds of disasters affect the contrast of electrical network ability, as shown in Figure 2.

From the preferred embodiment providing, to the application note of decision method that the present invention carries, can find out, according to implementation step provided by the present invention, by proposing 4, judge that disaster affects the index of electrical network, utilize fuzzy mathematics theory by its obfuscation, and respectively judgement index is carried out to weight analysis by analytical hierarchy process and Information Entropy, and the weight that two kinds of methods are tried to achieve is carried out comprehensively, in conjunction with method of weighted mean, having obtained disaster affects the comprehensive evaluation vector of electrical network ability, has reflected the capability of influence of disaster to electrical network comprehensively.

Specific embodiment described herein is only to the explanation for example of the present invention's spirit.Those skilled in the art can make various modifications or supplement or adopt similar mode to substitute described specific embodiment, but can't depart from spirit of the present invention or surmount the defined scope of appended claims.

Claims (7)

1. a disaster causes many index Fuzzies decision method of electric network fault, it is characterized in that, based on 4 kinds of disasters of definition, affect the judgement index of electrical network ability: tripping operation number of times, unplanned stoppage in transit number of times, region power transmission line comprehensive trip-out rate and reclosing failure rate, specifically comprise the following steps:

Step 1, the degree of membership based on fuzzy mathematics is theoretical, by described 4 kinds of judgement index Fuzzies, obtains normalized fuzzy overall evaluation matrix R;

Step 2, based on analytical hierarchy process, determines above-mentioned 4 main weights W of judging index;

Step 3, based on Information Entropy, determines the inferior weight V that respectively judges index according to 4 of obfuscation indexs;

Step 4, the inferior weight V that the main weights W obtaining based on step 2 and step 3 obtain, obtains the comprehensive weight vector C that judges index;

Step 5, based on method of weighted mean, the fuzzy overall evaluation matrix R obtaining according to step 1 and judgement index comprehensive weight vector C determine comprehensive evaluation result vector B.

2. a kind of disaster according to claim 1 causes many index Fuzzies decision method of electric network fault, it is characterized in that,

Described tripping operation number of times N _t(j) represent, specifically refer to the number of times that disaster j causes electrical network tripping operation every year, its unit is next year;

Described unplanned stoppage in transit number of times N _nPO(j) represent, specifically refer to the number of times that disaster j causes electrical network tripping operation every year, its unit is next year;

Described region power transmission line comprehensive trip-out rate R _cT(j) represent, based on following formula:

$R_{\mathrm{CT}}\left(j\right)=\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{\mathrm{\&alpha;}}_i{R}_{\mathrm{Ti}}\left(j\right)$

Wherein: α _ifor the weight of this electric pressure circuit, this coefficient is relevant with economic transmission capacity and the fed distance of transmission line of electricity; R _cT(j) be the trip-out rate of this electric pressure transmission line of electricity, unit is inferior/100 km years; R _cT(j) be region power transmission line comprehensive trip-out rate, unit is inferior/100 km years;

Wherein, trip-out rate is characterized by:

$R_{\mathrm{Ti}}\left(j\right)=\frac{N_{\mathrm{Ti}}\left(j\right)}{L}$

Wherein: L is the length of specific voltage grade transmission line of electricity, unit was 100 km years, R _ti(j) be the trip-out rate of this electric pressure transmission line of electricity, unit is inferior/100 km years, N _ti(j) be the tripping operation number of times of this electric pressure transmission line of electricity;

Described reclosing failure rate R _rF(j) represent, based on following formula:

$R_{\mathrm{RF}}\left(j\right)=\frac{N_{\mathrm{NPO}}\left(j\right)}{N_T}\&times;100\%$

Wherein, R _rF(j) the Closing fault rate of attaching most importance to, dimensionless; N _t(j) be tripping operation number of times; N _nPO(j) be the number of times of the unplanned stoppage in transit of transmission facility.

3. a kind of disaster according to claim 2 causes many index Fuzzies decision method of electric network fault, it is characterized in that, described 4 kinds of obfuscations of judging indexs are based on following formula:

${x_{\mathrm{ij}}}^s=\frac{x_{\mathrm{ij}}}{\underset{j\&Element;I}{\max }\left\{x_{\mathrm{ij}}\right\}+\underset{j\&Element;I}{\min }\left\{x_{\mathrm{ij}}\right\}}$

Wherein: for x _ij, i=1,2,3,4; J=1,2 ..., k, represents that i judgement of j kind disaster refers to target value, for x _ij ^s, i=1,2,3,4; J=1,2 ..., k, i the relative degree of membership value of judging index of expression j kind disaster, I represents disaster set to be evaluated;

Wherein: x _ijwith the above-mentioned 4 kinds relations of judging indexs, based on following formula:

x _1j=N _T（j）;

Wherein: N _t(j) be tripping operation number of times;

x _2j=N _NPO（j）;

Wherein: N _nPO(j) be the number of times of the unplanned stoppage in transit of transmission facility;

x _3j=R _CT（j）;

Wherein: R _cT(j) be region power transmission line comprehensive trip-out rate;

x _4j=R _RF（j）;

Wherein: R _rF(j) the Closing fault rate of attaching most importance to.

4. a kind of disaster according to claim 3 causes many index Fuzzies decision method of electric network fault, it is characterized in that, and the determining of normalized fuzzy overall evaluation matrix R in described step 1, based on following formula:

$r_{\mathrm{ij}}=\frac{{x_{\mathrm{ij}}}^s}{\underset{t=1}{\overset{j}{\mathrm{\&Sigma;}}}{x_{\mathrm{it}}}^s}.$

5. a kind of disaster according to claim 4 causes many index Fuzzies decision method of electric network fault, it is characterized in that, determining of the main weights W of judgement index based on analytical hierarchy process in described step 2, comprises the following steps:

Step 2.1, determine the quantitative criteria of index:

Main weights W by index i with respect to index j _ijby 1～9 scale, carry out quantification treatment, based on following formula:

w _ij=N

Wherein: w _ijfor the weight of index i with respect to index j, N is the integer in 1～9 scope;

Index j is with respect to the main weights W of index i _ji, based on following formula:

w _ji=1/w _ij

Step 2.2, determine initial flexible strategy:

According to above-mentioned formula, determine each factor x _i(i=1 ..., weight k), by the weight normalizing proposing, obtains weighted value and is

w wherein _virepresent that v estimates i the weight of judging index, w _vi' represent the respective weights estimated value after normalizing; Finally, calculate the mean value of the weight estimated value proposing

and as the weight of every judgement index;

Step 2.3, the determining of weight:

First, the weight of asking for according to above-mentioned steps is set up judgment matrix W, the element w that in W, i is capable and j is listed as _ijrepresent to judge index w _iand w _jthe scaling ratio of gained relatively; Secondly, the geometric mean of every each calibration data of a line in compute matrix W,

finally, be normalized, utilize w _i'=W _i/ ∑ W _i, determine and respectively judge the weight that index is final, form weight vector W'=[w ₁', w ₂' ... w _n'], wherein n represents to judge the number of index.

6. a kind of disaster according to claim 4 causes many index Fuzzies decision method of electric network fault, it is characterized in that, in described step 3, time weight V of the evaluation index based on Information Entropy determines, comprises the following steps:

Step 3.1, raw data matrix normalization:

If raw data matrix is A=(a _ij) _{k * n}, wherein k is for to judge that index n is as evaluation object; Judge that index is all that large person is excellent type, obtains normalization matrix based on following formula for 4:

$u_{\mathrm{ij}}=\frac{a_{\mathrm{ij}}}{\underset{1\&le;j\&le;n}{\max }\left\{a_{\mathrm{ij}}\right\}+\underset{1\&le;j\&le;n}{\min }\left\{a_{\mathrm{ij}}\right\}}$

Step 3.2, the determining of entropy:

The entropy of i index is based on following formula:

$e_i=-\frac{\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{f}_{\mathrm{ij}}1n{f}_{\mathrm{ij}}}{1\mathrm{nn}}$

Wherein: $f_{\mathrm{ij}}=u_{\mathrm{ij}}/\underset{j=1}{\overset{n}{\mathrm{\&Sigma;}}}{u}_{\mathrm{ij}};$

Step 3.3, the determining of weight:

After having determined the entropy of i index, the determining based on following formula of i index weights:

$v_i=\frac{1-e_i}{k-\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{e}_i}(0\&le;v_i\&le;1,\underset{1}{\overset{k}{\mathrm{\&Sigma;}}}{v}_i=1)$

In above-mentioned a kind of disaster, cause many index Fuzzies decision method of electric network fault, the comprehensive weight vector C of described judgement index determines based on following formula:

$c_i=w_i^{`}{v}_i/\underset{i=1}{\overset{k}{\mathrm{\&Sigma;}}}{w}_i^{`}{v}_i(i=\mathrm{1,2},....k)$

Wherein: w _iand v _ithe every judgement index weights that is respectively analytical hierarchy process and Information Entropy calculating gained, comprehensive weight vector is C=(c _i, c ₂c _k).

7. a kind of disaster according to claim 4 causes many index Fuzzies decision method of electric network fault, it is characterized in that the determining based on following formula of the described comprehensive evaluation result vector based on method of weighted mean:

B=C·R

Wherein: B is comprehensive evaluation result vector, C is comprehensive weight vector, and R is fuzzy overall evaluation matrix.

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