CN104361250A - Photovoltaic grid connected safety evaluation method - Google Patents

Abstract

The invention discloses a photovoltaic grid connected safety evaluation method, which comprises the following steps of step 1, selecting a photovoltaic power station grid connected safety evaluation index, and building an evaluation matrix according to the index; step 2, carrying out index syntropy processing and dimensionless processing on the evaluation matrix to obtain a standard evaluation matrix; step 3, confirming the evaluation matrix and an index weight vector based on an analytic hierarchy process; step 4, utilizing a method of distance of good-bad solutions to calculate relative proximity corresponding to each photovoltaic power station, and realizing comprehensive evaluation on photovoltaic power station grid connected safety through sorting of the relative proximities. The photovoltaic grid connected safety evaluation method can comprehensively and objectively evaluate the safety running conditions of the photovoltaic power station grid connection, and provides the evaluation basis for the photovoltaic power generation grid connected safety conditions for an electric power department.

Description

A kind of grid-connected method for evaluating safety

Technical field

The invention belongs to grid-connected safety evaluatio technical field, relate to a kind of grid-connected method for evaluating safety, be specifically related to a kind of based on analytical hierarchy process and the good and bad grid-connected method for evaluating safety separating Furthest Neighbor.

Background technology

Development distributed photovoltaic power generation, to optimizing China's energy structure, realizing energy supply diversification, tackle climate change, preserve the ecological environment, promoting that the sustainable development of socio-economy has a very important role, is also the basic demand of implementing a scientific outlook on development, building a resource-conserving society simultaneously.From fast development and the photovoltaic plant high accident rate of solar energy power generating, the security of Solar use is very important.The security of Solar use not only can make a big impact to operation of power networks economy, and can limit the development of photovoltaic generation to a certain extent.Meanwhile, due to the intermittence of photovoltaic generation and the otherness of regional sun power, the security of different photovoltaic electric station grid connection is difficult to compare.

Summary of the invention

For the deficiencies in the prior art, the object of this invention is to provide a kind of based on analytical hierarchy process and the good and bad grid-connected method for evaluating safety separating Furthest Neighbor, the method evaluates the safe operation situation of photovoltaic electric station grid connection comprehensively, objectively, for power department provides Appreciation gist to photovoltaic power generation grid-connecting safety conditions.

The technical solution adopted in the present invention is: a kind of grid-connected method for evaluating safety, is characterized in that, comprise the following steps:

Step 1: choose photovoltaic electric station grid connection Safety Evaluation Index, according to this Index Establishment Evaluations matrix;

Step 2: index is carried out to Evaluations matrix and changes process in the same way and go dimension process, obtain standard evaluation matrix;

Step 3: based on analytical hierarchy process determination Evaluations matrix and index weights vector;

Step 4: utilize good and bad Furthest Neighbor of separating to calculate relative proximities corresponding to each photovoltaic plant, and realize the comprehensive evaluation to photovoltaic electric station grid connection security by the sequence of relative proximities.

As preferably, the photovoltaic electric station grid connection Safety Evaluation Index described in step 1 comprises photovoltaic and to dissolve capacity limit, short-circuit current rate of growth, percent harmonic distortion, rate of qualified voltage, voltage fluctuation rate, SVC/SVG dynamic response performance; Wherein:

(1) photovoltaic is dissolved capacity: be incorporated into the power networks to realize distributed photovoltaic power plant safety, national grid has made relevant regulations to the photovoltaic capacity of dissolving; Wherein single-point photovoltaic capacity of dissolving is determined according to distributed photovoltaic modular design criterion; When photovoltaic T connects, the photovoltaic capacity of each circuit no more than circuit with peak load 60%, when photovoltaic adopts access via telephone line, its capacity adopts the 6MW specified in modular design; The substation photovoltaic capacity of dissolving must not exceed 25% of substation's band peak load;

(2) short-circuit current rate of growth: grid short circuit electric current Growth Rate Calculation formula is as follows

$I_{\mathrm{UP}}\%=\frac{I_{\mathrm{BE}}-I_{\mathrm{AE}}}{I_{\mathrm{AE}}}$

Wherein, I _aEfor short-circuit current before photovoltaic access; I _bEfor short-circuit current after photovoltaic access; I _uP% is short-circuit current rate of growth;

(3) percent harmonic distortion: the computing formula of percent harmonic distortion is as follows

$U_b=\sqrt{\underset{n=2}{\overset{\∞}{\mathrm{\Σ}}}{U}_n^2}$

$\mathrm{THD}=\frac{U_b}{U_1}\×100\%$

Wherein U _bfor voltage total harmonic distortion, THD is percent harmonic distortion, U ₁for fundamental voltage effective value, U _nfor each harmonic voltage effective value, n gets infinity from 2;

(4) rate of qualified voltage: the computing formula of rate of qualified voltage is as follows

$U\%=1-\frac{T_1}{T_2}$

Wherein, U% represents rate of qualified voltage; T ₁represent the voltage overtime; T ₂represent voltage detecting T.T.;

(5) voltage fluctuation rate: the computing formula of voltage fluctuation rate is as follows

$U_V\%=\frac{\left|U_t\right|}{U_0}$

Wherein, | U _t| represent the absolute value of voltage fluctuation difference, U ₀represent voltage duration, U _v% represents voltage fluctuation rate;

(6) SVC/SVG dynamic response performance: according to and the change in voltage of site, judge that can dynamic reactive compensation device SVC/SVG meet regulatory requirements in the continuous working period after change in voltage; Record the situation up to standard of reactive power compensator in month, can realize the evaluation to reactive power compensator in month, evaluation index RP is: RP=G/H; Wherein RP represents compliance rate, and G represents the number of times up to standard in the unit interval, and H represents the total degree that needs compensate.

As preferably, described in step 1, set up Evaluations matrix, its Evaluations matrix Y=(Y ₁, Y ₂, Y ₃, Y ₄, Y ₅, Y ₆), Y ₁for photovoltaic is dissolved capacity limit, Y ₂for short-circuit current rate of growth, Y ₃for percent harmonic distortion, Y ₄for rate of qualified voltage, Y ₅for voltage fluctuation rate, Y ₆for SVC/SVG dynamic response performance.

As preferably, carrying out index to Evaluations matrix and change process in the same way described in step 2, its specific implementation process is first structural matrix Y '=(y _ij) _{m × n}, wherein m is the number of evaluation index, and n evaluates individual number; Because short-circuit current rate of growth, percent harmonic distortion, voltage fluctuation rate are negative index, therefore process is changed in the same way to it be converted into direct index; The computing formula that negative index is converted into direct index is as follows:

$Y_i^{\′}=\frac{1}{k+\max \left|Y_i\right|+Y_i},i=\mathrm{1,2}...m$

Wherein, y _ijrepresent the matrix element carrying out index and change in the same way, maxY _irepresent indicator vector Y _ithe maximal value of middle element, k value gets 0.1.

Evaluation index is divided three classes: direct index, negative index and interval index, and direct index represents that desired value larger reflection situation is more excellent; Negative index expression index larger reflection situation is more excellent; Interval index expression index situation in specified scope is optimum.

As preferably, go dimension process described in step 2 to Evaluations matrix, its detailed process is to matrix Y ' _icarry out nondimensionalization process, turn to canonical matrix Y " _i; Wherein carry out the matrix element y of dimension process " _ijaccount form is as follows

$y_{\mathrm{ij}}^{\′\′}=\frac{y_{\mathrm{ij}}}{\sqrt{\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{y}_{\mathrm{ij}}^2}},i=\mathrm{1,2}...m.$

As preferably, described in step 3 based on analytical hierarchy process determination Evaluations matrix and index weights vector, its specific implementation comprises following sub-step:

Step 3.1: determine target and factor of evaluation: choose 6 evaluation indexes that photovoltaic plant runs, then evaluation vector u={u ₁, u ₂..., u ₆; u ₁, u ₂..., u ₆represent the evaluation index of 6 described in step 1 respectively;

Step 3.2: Judgement Matricies S=(u _ij) _{p × p}, wherein p is index number;

Step 3.3: the Maximum characteristic root λ calculating judgment matrix S _max, and characteristic of correspondence vector A, proper vector A are the importance ranking of a factor of evaluation, are an evaluation criterion weight and distribute;

Step 3.4: the consistency check of judgment matrix S; Determine coincident indicator CI=(λ _max-n)/(n-1) and Aver-age Random Consistency Index RI, the i.e. average of CI; When random Consistency Ratio time, then the result of step analysis sequence meets consistance, and each judge index weight allocation is rational; Otherwise, again to redistribute each index weights to the evaluation element value of judgment matrix.

As preferably, quality solution Furthest Neighbor described in step 4 refers to determines reference point in space, comprising optimum point and the most bad point, then calculates the distance of each evaluation object and reference point, higher with the nearlyer security of optimum point, higher with the security far away of the most bad distance; Calculate the relative proximities of sample point to optimum sample point according to quality solution Furthest Neighbor, realize the evaluation to grid-connected security finally by the relative proximities sequence calculated, relative proximities solves as follows:

Relative proximities C _jcalculating formula:

Wherein, C _jrepresent the relative proximities of sample point to optimum sample point; represent the distance of sample point to the most bad point; represent the distance of sample point to optimum point;

After utilizing Weight of Coefficient through Analytic Hierarchy Process, according to following formula determination weighted data matrix Y " ':

Y″′＝Y″ _i·ω _i,i＝1,2…m

Wherein, ω _irepresent the weight of each evaluation index;

Form optimum ideal sample by the maximal value of evaluation index each in all samples, form the most bad ideal sample by the minimum value of an evaluation index, use Y respectively ⁺and Y ^-represent:

Sample is to the distance of optimum point $D_j^{+}=\sqrt{\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{(y_{\mathrm{ij}}-y_i^{+})}^2},j=\mathrm{1,2},...n$

Sample is to the distance of the most bad point $D_j^{-}=\sqrt{\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{(y_{\mathrm{ij}}-y_i^{-})}^2},j=\mathrm{1,2},...n$

According to relative proximities C _jsize each evaluation object is sorted, C _jthe relative distance of larger expression evaluation object and ideal sample is less, and evaluation result is better.

Compared with the prior art, advantage of the present invention is:

1, the present invention proposes analytical hierarchy process to be used for the weight calculating grid-connected safe operation index.Grid-connected safe operation index is divided into some levels by the method, and judgement is compared to the significance level between two two indexes, after setting up judgment matrix, obtain by the proper vector and eigenvalue of maximum calculating judgment matrix the weight phasor reflecting different index significance level.Analytical hierarchy process is by organically combining quantitative analysis method and method for qualitative analysis, and quantitative test goes out the influence degree of each index to evaluation result exactly, and algorithm is simply clear and definite and practical;

2, quality is separated the comprehensive evaluation that Furthest Neighbor is used for realizing grid-connected safe operation situation by the present invention's proposition.The method, by determining reference point at higher dimensional space, comprises optimum point and the most bad point, then calculates the distance of each evaluation object index and optimum point or the most bad point.The distance of grid-connected Safety Evaluation Index and optimum point is less or larger with the distance of the most bad point, illustrates that to be evaluated grid-connected combination property more excellent, otherwise poorer.Finally, gained distance is utilized to calculate the relative proximities of sample point to optimum sample point, and then by realizing the comprehensive evaluation of Operation of Wind Power Plant to degree of closeness sequence.Good and bad Furthest Neighbor of separating is weighted process according to the overlaps of index to it, be applicable to dynamic and the relativity feature of different photovoltaic electric station grid connection runnability, therefore the method can determine quantitative analysis foundation for the evaluation comparison of different photovoltaic electric station grid connection performance provides;

3, the grid-connected method for evaluating safety based on analytical hierarchy process and good and bad solution Furthest Neighbor provided by the invention evaluates grid-connected safe operation situation comprehensively, objectively, provides Appreciation gist for power department carries out Integrated comparative to photovoltaic plant ruuning situation.

Accompanying drawing explanation

Fig. 1: be process flow diagram of the present invention.

Embodiment

Understand for the ease of those of ordinary skill in the art and implement the present invention, below in conjunction with drawings and Examples, the present invention is described in further detail, should be appreciated that exemplifying embodiment described herein is only for instruction and explanation of the present invention, is not intended to limit the present invention.

Analytical hierarchy process (be called for short AHP) is filled in the base of a fruit 20 century 70 mid-terms formally proposed by the U.S. scholar Thomas that plans strategies for, it is that a kind of quantitative and qualitative analysis combines, systematization, stratification analytical approach.The method is divided into each factor in challenge some levels of interkniting and makes it methodization, according to the fuzzy Judgment to objective reality, with regard to the expression of the relative importance quantitative of each level, recycling mathematical method determines the weight of whole element relative importance order.Due to the practicality in the decision problem of process complexity and validity, it is applied in multiple field.

Good and bad solution Furthest Neighbor regards evaluation object as the variable on coordinate, geometrically forming one with evaluation object index for coordinate axis sunlight higher dimensional space, each point being evaluated to as if being determined in this space by its multiple desired values of reflection viewed from geometric angle, by comparing to these spatial point and optimum point or the most bad some distance the comprehensive evaluation realized being evaluated object.The optimal value of index is the desirable level of evaluation this index interior in period, the relative superior or inferior degree of each operating index of wind energy turbine set can be judged by the difference calculating grid-connected security operating index value and desirable level, and then can according to the comprehensive evaluation of indices situation realization to grid-connected security situation.

Ask for an interview Fig. 1, provided by the invention based on analytical hierarchy process and the good and bad grid-connected method for evaluating safety separating Furthest Neighbor, comprise the steps:

Step 1: choose photovoltaic electric station grid connection Safety Evaluation Index, according to this Index Establishment Evaluations matrix;

Wherein photovoltaic electric station grid connection Safety Evaluation Index comprises photovoltaic and to dissolve capacity limit, short-circuit current rate of growth, percent harmonic distortion, rate of qualified voltage, voltage fluctuation rate, SVC/SVG dynamic response performance; Wherein:

(1) photovoltaic is dissolved capacity: be incorporated into the power networks to realize distributed photovoltaic power plant safety, national grid has made relevant regulations to the photovoltaic capacity of dissolving; Wherein single-point photovoltaic capacity of dissolving is determined according to distributed photovoltaic modular design criterion; When photovoltaic T connects, the photovoltaic capacity of each circuit no more than circuit with peak load 60%, when photovoltaic adopts access via telephone line, its capacity adopts the 6MW specified in modular design; The substation photovoltaic capacity of dissolving must not exceed 25% of substation's band peak load;

(2) short-circuit current rate of growth: grid short circuit electric current Growth Rate Calculation formula is as follows

$I_{\mathrm{UP}}\%=\frac{I_{\mathrm{BE}}-I_{\mathrm{AE}}}{I_{\mathrm{AE}}}$

Wherein, I _aEfor short-circuit current before photovoltaic access; I _bEfor short-circuit current after photovoltaic access; I _uP% is short-circuit current rate of growth;

(3) percent harmonic distortion: the computing formula of percent harmonic distortion is as follows

$U_b=\sqrt{\underset{n=2}{\overset{\∞}{\mathrm{\Σ}}}{U}_n^2}$

$\mathrm{THD}=\frac{U_b}{U_1}\×100\%$

Wherein U _bfor voltage total harmonic distortion, THD is percent harmonic distortion, U ₁for fundamental voltage effective value, U _nfor each harmonic voltage effective value, n gets infinity from 2;

(4) rate of qualified voltage: the computing formula of rate of qualified voltage is as follows

$U\%=1-\frac{T_1}{T_2}$

Wherein, U% represents rate of qualified voltage; T ₁represent the voltage overtime; T ₂represent voltage detecting T.T.;

(5) voltage fluctuation rate: the computing formula of voltage fluctuation rate is as follows

$U_V\%=\frac{\left|U_t\right|}{U_0}$

Wherein, | U _t| represent the absolute value of voltage fluctuation difference, U ₀represent voltage duration, U _v% represents voltage fluctuation rate;

(6) SVC/SVG dynamic response performance: according to and the change in voltage of site, judge that can dynamic reactive compensation device SVC/SVG meet regulatory requirements in the continuous working period after change in voltage; Record the situation up to standard of reactive power compensator in month, can realize the evaluation to reactive power compensator in month, evaluation index RP is: RP=G/H; Wherein RP represents compliance rate, and G represents the number of times up to standard in the unit interval, and H represents the total degree that needs compensate.

Its Evaluations matrix Y=(Y ₁, Y ₂, Y ₃, Y ₄, Y ₅, Y ₆), Y ₁for photovoltaic is dissolved capacity limit, Y ₂for short-circuit current rate of growth, Y ₃for percent harmonic distortion, Y ₄for rate of qualified voltage, Y ₅for voltage fluctuation rate, Y ₆for SVC/SVG dynamic response performance.

Step 2: index is carried out to Evaluations matrix and changes process in the same way and go dimension process, obtain standard evaluation matrix;

Wherein carry out index to Evaluations matrix and change process in the same way, its specific implementation process is first structural matrix Y '=(y _ij) _{m × n}, wherein m is the number of evaluation index, and n evaluates individual number; Because short-circuit current rate of growth, percent harmonic distortion, voltage fluctuation rate are negative index, therefore process is changed in the same way to it be converted into direct index; The computing formula that negative index is converted into direct index is as follows:

$Y_i^{\′}=\frac{1}{k+\max \left|Y_i\right|+Y_i},i=\mathrm{1,2}...m$

Wherein, y _ijrepresent the matrix element carrying out index and change in the same way, maxY _irepresent indicator vector Y _ithe maximal value of middle element, k value gets 0.1.

Evaluation index is divided three classes: direct index, negative index and interval index, and direct index represents that desired value larger reflection situation is more excellent; Negative index expression index larger reflection situation is more excellent; Interval index expression index situation in specified scope is optimum.

Wherein go dimension process to Evaluations matrix, its detailed process is to matrix Y ' _icarry out nondimensionalization process, turn to canonical matrix Y " _i; Wherein carry out the matrix element y of dimension process " _ijaccount form is as follows

$y_{\mathrm{ij}}^{\′\′}=\frac{y_{\mathrm{ij}}}{\sqrt{\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{y}_{\mathrm{ij}}^2}},i=\mathrm{1,2}...m.$

Step 3: based on analytical hierarchy process determination Evaluations matrix and index weights vector; Its specific implementation comprises following sub-step:

Step 3.1: determine target and factor of evaluation: choose 6 evaluation indexes that photovoltaic plant runs, then evaluation vector u={u ₁, u ₂..., u ₆; u ₁, u ₂..., u ₆represent the evaluation index of 6 described in step 1 respectively;

Step 3.2: Judgement Matricies S=(u _ij) _{p × p}, wherein p is index number;

Step 3.3: the Maximum characteristic root λ calculating judgment matrix S _max, and characteristic of correspondence vector A, proper vector A are the importance ranking of a factor of evaluation, are an evaluation criterion weight and distribute;

Step 3.4: the consistency check of judgment matrix S; Determine coincident indicator CI=(λ _max-n)/(n-1) and Aver-age Random Consistency Index RI, the i.e. average of CI; When random Consistency Ratio time, then the result of step analysis sequence meets consistance, and each judge index weight allocation is rational; Otherwise, again to redistribute each index weights to the evaluation element value of judgment matrix.

Step 4: utilize good and bad Furthest Neighbor of separating to calculate relative proximities corresponding to each photovoltaic plant, and realize the comprehensive evaluation to photovoltaic electric station grid connection security by the sequence of relative proximities;

Good and bad solution Furthest Neighbor refers to determines reference point in space, comprising optimum point and the most bad point, then calculates the distance of each evaluation object and reference point, higher with the nearlyer security of optimum point, higher with the security far away of the most bad distance; Calculate the relative proximities of sample point to optimum sample point according to quality solution Furthest Neighbor, realize the evaluation to grid-connected security finally by the relative proximities sequence calculated, relative proximities solves as follows:

Relative proximities C _jcalculating formula:

Wherein, C _jrepresent the relative proximities of sample point to optimum sample point; represent the distance of sample point to the most bad point; represent the distance of sample point to optimum point;

After utilizing Weight of Coefficient through Analytic Hierarchy Process, according to following formula determination weighted data matrix Y " ':

Y″′＝Y″ _i·ω _i,i＝1,2…m

Wherein, ω _irepresent the weight of each evaluation index;

Form optimum ideal sample by the maximal value of evaluation index each in all samples, form the most bad ideal sample by the minimum value of an evaluation index, use Y respectively ⁺and Y ^-represent:

Sample is to the distance of optimum point $D_j^{+}=\sqrt{\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{(y_{\mathrm{ij}}-y_i^{+})}^2},j=\mathrm{1,2},...n$

Sample is to the distance of the most bad point $D_j^{-}=\sqrt{\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{(y_{\mathrm{ij}}-y_i^{-})}^2},j=\mathrm{1,2},...n$

According to relative proximities C _jsize each evaluation object is sorted, C _jthe relative distance of larger expression evaluation object and ideal sample is less, and evaluation result is better.

In test process, the present invention have selected some typical light overhead utilities data that are incorporated into the power networks and has carried out a large amount of tests.Can be found out by test result, propose the effective evaluation that can realize grid-connected security based on analytical hierarchy process and the good and bad grid-connected method for evaluating safety separating Furthest Neighbor.

Should be understood that, the part that this instructions does not elaborate all belongs to prior art.

Should be understood that; the above-mentioned description for preferred embodiment is comparatively detailed; therefore the restriction to scope of patent protection of the present invention can not be thought; those of ordinary skill in the art is under enlightenment of the present invention; do not departing under the ambit that the claims in the present invention protect; can also make and replacing or distortion, all fall within protection scope of the present invention, request protection domain of the present invention should be as the criterion with claims.

Claims (7)

1. a grid-connected method for evaluating safety, is characterized in that, comprises the following steps:

Step 1: choose photovoltaic electric station grid connection Safety Evaluation Index, according to this Index Establishment Evaluations matrix;

Step 2: index is carried out to Evaluations matrix and changes process in the same way and go dimension process, obtain standard evaluation matrix;

Step 3: based on analytical hierarchy process determination Evaluations matrix and index weights vector;

Step 4: utilize good and bad Furthest Neighbor of separating to calculate relative proximities corresponding to each photovoltaic plant, and realize the comprehensive evaluation to photovoltaic electric station grid connection security by the sequence of relative proximities.

2. grid-connected method for evaluating safety according to claim 1, is characterized in that: the photovoltaic electric station grid connection Safety Evaluation Index described in step 1 comprises photovoltaic and to dissolve capacity limit, short-circuit current rate of growth, percent harmonic distortion, rate of qualified voltage, voltage fluctuation rate, SVC/SVG dynamic response performance; Wherein:

(1) photovoltaic is dissolved capacity: be incorporated into the power networks to realize distributed photovoltaic power plant safety, single-point photovoltaic capacity of dissolving is determined according to distributed photovoltaic modular design criterion; When photovoltaic T connects, the photovoltaic capacity of each circuit no more than circuit with peak load 60%, when photovoltaic adopts access via telephone line, its capacity adopts the 6MW specified in modular design; The substation photovoltaic capacity of dissolving must not exceed 25% of substation's band peak load;

(2) short-circuit current rate of growth: grid short circuit electric current Growth Rate Calculation formula is as follows

$I_{\mathrm{UP}}\%=\frac{I_{\mathrm{BE}}-I_{\mathrm{AE}}}{I_{\mathrm{AE}}}$

Wherein, I _aEfor short-circuit current before photovoltaic access; I _bEfor short-circuit current after photovoltaic access; I _uP% is short-circuit current rate of growth;

(3) percent harmonic distortion: the computing formula of percent harmonic distortion is as follows

$U_b=\sqrt{\underset{n=2}{\overset{\∞}{\mathrm{\Σ}}}{U}_n^2}$

$\mathrm{THD}=\frac{U_b}{U_1}\×100\%$

Wherein U _bfor voltage total harmonic distortion, THD is percent harmonic distortion, U ₁for fundamental voltage effective value, U _nfor each harmonic voltage effective value, n gets infinity from 2;

(4) rate of qualified voltage: the computing formula of rate of qualified voltage is as follows

$U\%=1-\frac{T_1}{T_2}$

Wherein, U% represents rate of qualified voltage; T ₁represent the voltage overtime; T ₂represent voltage detecting T.T.;

(5) voltage fluctuation rate: the computing formula of voltage fluctuation rate is as follows

$U_V\%=\frac{\left|U_t\right|}{U_0}$

Wherein, | U _t| represent the absolute value of voltage fluctuation difference, U ₀represent voltage duration, U _v% represents voltage fluctuation rate;

(6) SVC/SVG dynamic response performance: according to and the change in voltage of site, judge that can dynamic reactive compensation device SVC/SVG meet regulatory requirements in the continuous working period after change in voltage; Record the situation up to standard of reactive power compensator in month, can realize the evaluation to reactive power compensator in month, evaluation index RP is: RP=G/H; Wherein RP represents compliance rate, and G represents the number of times up to standard in the unit interval, and H represents the total degree that needs compensate.

3. grid-connected method for evaluating safety according to claim 1, is characterized in that: set up Evaluations matrix, its Evaluations matrix Y=(Y described in step 1 ₁, Y ₂, Y ₃, Y ₄, Y ₅, Y ₆), Y ₁for photovoltaic is dissolved capacity limit, Y ₂for short-circuit current rate of growth, Y ₃for percent harmonic distortion, Y ₄for rate of qualified voltage, Y ₅for voltage fluctuation rate, Y ₆for SVC/SVG dynamic response performance.

4. grid-connected method for evaluating safety according to claim 3, is characterized in that: carrying out index to Evaluations matrix and change process in the same way described in step 2, and its specific implementation process is first structural matrix Y '=(y _ij) _{m × n}, wherein m is the number of evaluation index, and n evaluates individual number; Because short-circuit current rate of growth, percent harmonic distortion, voltage fluctuation rate are negative index, therefore process is changed in the same way to it be converted into direct index; The computing formula that negative index is converted into direct index is as follows:

$Y_i^{\′}=\frac{1}{k+\max \left|Y_i\right|+Y_i},i=\mathrm{1,2}...m$

Wherein, y _ijrepresent the matrix element carrying out index and change in the same way, max Y _irepresent indicator vector Y _ithe maximal value of middle element, k value gets 0.1.

5. grid-connected method for evaluating safety according to claim 4, is characterized in that: go dimension process to Evaluations matrix described in step 2, and its detailed process is to matrix Y ' _icarry out nondimensionalization process, turn to canonical matrix Y " _i; Wherein carry out the matrix element y of dimension process " _ijaccount form is as follows

$y_{\mathrm{ij}}^{\′\′}=\frac{y_{\mathrm{ij}}}{\sqrt{\underset{j=1}{\overset{n}{\mathrm{\Σ}}}{y}_{\mathrm{ij}}^2}},i=\mathrm{1,2}...m.$

6. grid-connected method for evaluating safety according to claim 2, is characterized in that: described in step 3 based on analytical hierarchy process determination Evaluations matrix and index weights vector, its specific implementation comprises following sub-step:

Step 3.1: determine target and factor of evaluation: choose 6 evaluation indexes that photovoltaic plant runs, then evaluation vector u={u ₁, u ₂..., u ₆; u ₁, u ₂..., u ₆represent the evaluation index of 6 described in step 1 respectively;

Step 3.2: Judgement Matricies S=(u _ij) _{p × p}, wherein p is index number;

Step 3.3: the Maximum characteristic root λ calculating judgment matrix S _max, and characteristic of correspondence vector A, proper vector A are the importance ranking of a factor of evaluation, are an evaluation criterion weight and distribute;

Step 3.4: the consistency check of judgment matrix S; Determine coincident indicator CI=(λ _max-n)/(n-1) and Aver-age Random Consistency Index RI, the i.e. average of CI; When random Consistency Ratio time, then the result of step analysis sequence meets consistance, and each judge index weight allocation is rational; Otherwise, again to redistribute each index weights to the evaluation element value of judgment matrix.

7. grid-connected method for evaluating safety according to claim 4, it is characterized in that: the quality solution Furthest Neighbor described in step 4 refers to determines reference point in space, comprising optimum point and the most bad point, then the distance of each evaluation object and reference point is calculated, higher with the nearlyer security of optimum point, higher with the security far away of the most bad distance; Calculate the relative proximities of sample point to optimum sample point according to quality solution Furthest Neighbor, realize the evaluation to grid-connected security finally by the relative proximities sequence calculated, relative proximities solves as follows:

Relative proximities C _jcalculating formula: $C_j=\frac{D_j^{-}}{D_j^{-}+D_j^{+}};$

Wherein, C _jrepresent the relative proximities of sample point to optimum sample point; represent the distance of sample point to the most bad point; represent the distance of sample point to optimum point;

After utilizing Weight of Coefficient through Analytic Hierarchy Process, according to following formula determination weighted data matrix Y " ':

Y″′＝Y″ _i·ω _i,i＝1,2...m

Wherein, ω _irepresent the weight of each evaluation index;

Form optimum ideal sample by the maximal value of evaluation index each in all samples, form the most bad ideal sample by the minimum value of an evaluation index, use Y respectively ⁺and Y ^-represent:

Sample is to the distance of optimum point $D_j^{+}=\sqrt{\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{(y_{\mathrm{ij}}-y_j^{+})}^2},j=\mathrm{1,2},...n$

Sample is to the distance of the most bad point $D_j^{-}=\sqrt{\underset{i=1}{\overset{m}{\mathrm{\Σ}}}{(y_{\mathrm{ij}}-y_i^{-})}^2},j=\mathrm{1,2},...n$

According to relative proximities C _jsize each evaluation object is sorted, C _jthe relative distance of larger expression evaluation object and ideal sample is less, and evaluation result is better.