CN106096765A - The evaluation methodology of distributing wind power group Optimal Transmission Expansion Planning scheme - Google Patents

Abstract

The invention discloses the evaluation methodology of a kind of distributing wind power group Optimal Transmission Expansion Planning scheme, including obtaining scheme to be evaluated and setting evaluation index；Evaluation index is given a mark by expert group, obtains decision matrix；Calculate subjectivity and the objective weight of each evaluation index；Determine the optimum combination weight of evaluation index；Use method for optimizing based on grey correlation analysis to carry out scheme preferred, obtain optimal distributing wind power group Optimal Transmission Expansion Planning scheme.The present invention is according to the impact on power system of each candidate scheme, calculate subjective weight and the objective weight of each evaluation index, so that it is determined that the weight of each evaluation index, gray relative analysis method and cosine ranking method are combined and each Optimal Transmission Expansion Planning scheme is carried out preferably and obtain optimal Optimal Transmission Expansion Planning scheme, therefore the present invention can evaluate each candidate scheme accurately, and methodological science, reliable, provide a set of analysis method brand-new, science to the evaluation of distributing wind power group Optimal Transmission Expansion Planning scheme.

Description

The evaluation methodology of distributing wind power group Optimal Transmission Expansion Planning scheme

Technical field

Present invention relates particularly to the evaluation methodology of a kind of distributing wind power group Optimal Transmission Expansion Planning scheme.

Background technology

Along with development and the raising of people's living standard of economic technology, environmental problem has had become as global asking Topic, therefore sustainable development idea becomes the common recognition of whole world people.

Wind energy, because of its environmental protection and energy saving, the feature such as operating cost is stable, distribution is extensive, is increasingly becoming China, or even The important component part of energy sustainable development strategy in global range.The distributings such as mountain region, China inland wind-powered electricity generation, lake region wind-powered electricity generation Wind power group, has the features such as wind-powered electricity generation has a very wide distribution, single wind-powered electricity generation capacity is little.Present domestic wind-powered electricity generation is in a high speed development Phase, major part inland wind-powered electricity generation will develop successively, and wind power group Optimal Transmission Expansion Planning research to be wind-powered electricity generation can reliably send and dissolve Basis.

Present Domestic is outer has preferably carried out extensively in-depth study to wind power integration electrical network and Optimal Transmission Expansion Planning scheme.But Research for wind-powered electricity generation is concentrated mainly on the large-scale wind power access impact on power system, and large-scale wind power accesses and dispersion Formula wind power integration is different for the impact of power system, and the most current research method and achievement in research are not suitable for evaluating dispersion The impact on accessing power system of the formula wind-powered electricity generation.And currently also there is no method or achievement in research to distributing wind-powered electricity generation Optimal Transmission Expansion Planning and right The impact accessing power system is evaluated.

Summary of the invention

It is an object of the invention to provide the impact of a kind of power system for distributing wind-powered electricity generation Optimal Transmission Expansion Planning on accessing The evaluation methodology of the distributing wind power group Optimal Transmission Expansion Planning scheme being evaluated.

The evaluation methodology of this distributing wind power group Optimal Transmission Expansion Planning scheme that the present invention provides, comprises the steps:

S1. distributing wind power group Optimal Transmission Expansion Planning scheme to be evaluated is obtained, and according to distributing wind power group Optimal Transmission Expansion Planning side The characteristic of case and power system obtains evaluation index；

S2. to distributing wind power group Optimal Transmission Expansion Planning scheme to be evaluated, use expert group that evaluation index is given a mark, obtain Decision matrix；

S3. subjective weight and the objective weight of each evaluation index are calculated；

S4. the optimum combination weight determining evaluation index based on the combination weighting method that moments estimation is theoretical is used；

S5. the optimum combination weight obtained according to step S4, uses the method for optimizing side of carrying out based on grey correlation analysis Case is preferred, obtains optimal distributing wind power group Optimal Transmission Expansion Planning scheme.

Evaluation index described in step S1 includes economy, safety and three indexs of adaptability；Wherein economic index Including once investing and energy loss expense；Safety indexes includes trend distribution, bus nodes voltage levvl, voltage stabilization Property, N-1 check, transient stability check and the penetration limit；Adaptive criteria includes region electricity needs, sends reliably Property, implement difficulty, transition difficulty, development adaptability and near region dispatching of power netwoks run.

The subjective weight of the evaluation index described in step S3 and objective weight, consult based on analytic hierarchy process (AHP) and expert for using The subjective weights method of inquiry method calculates the subjective weight of each evaluation index, uses based on independent information data fluctuations method and entropy assessment Objective Weighting calculate each evaluation index objective weight.

The combination weighting method theoretical based on moments estimation described in step S4, concretely comprises the following steps:

1) from subjective weight totally p sample of extraction, objective weight totally in extracts k-p sample, and assume that m is individual The combining weights vector of evaluation index is W=[ω₁,ω₂,…,ω_m], wherein k and p is natural number, and k ＞ p；

2) for jth evaluation index, subjective weight g of following formula parameter is used_jsWith objective weight g_jtPhase Prestige value:

$\left\{\begin{array}{cc}E\left(g_{js}\right)=\frac{\underset{s=1}{\overset{p}{\Σ}}{g}_{js}}{p}& (1\≤s\≤p)\\ E\left(g_{jt}\right)=\frac{\underset{t=1}{\overset{k-p}{\Σ}}{g}_{jt}}{k-p}& (1\≤t\≤k-p)\end{array}\right.$

3) for jth index, its important coefficient subjective, objective is respectively as follows:

$\left\{\begin{array}{c}{\mathrm{\α}}_j=\frac{E\left(g_{js}\right)}{E\left(g_{js}\right)+E\left(g_{jt}\right)}\\ {\mathrm{\β}}_j=\frac{E\left(g_{jt}\right)}{E\left(g_{js}\right)+E\left(g_{jt}\right)}\end{array}\right.$

4) according to the following formula to main, objective important coefficient in aggregative indicator:

$\left\{\begin{array}{c}\mathrm{\α}=\frac{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\α}}_j}{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\α}}_j+\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\β}}_j}=\frac{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\α}}_j}{m}\\ \mathrm{\β}=\frac{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\β}}_j}{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\α}}_j+\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\β}}_j}=\frac{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\β}}_j}{m}\end{array}\right.$

5) comprehensive weight of each evaluation index in the seismic responses calculated comprehensive weight vector of following combining weights is used ω_j:

$\left\{\begin{array}{cc}\min & B=\underset{s=1}{\overset{p}{\Σ}}\underset{j=1}{\overset{m}{\Σ}}\mathrm{\α}{(g_{js}-{\mathrm{\ω}}_j)}^2+\underset{t=1}{\overset{k-p}{\Σ}}\underset{j=1}{\overset{m}{\Σ}}\mathrm{\β}{(g_{jt}-{\mathrm{\ω}}_j)}^2\\ s.t.& \underset{j=1}{\overset{m}{\Σ}}{\mathrm{\ω}}_j=1,0\≤{\mathrm{\ω}}_j\≤1\end{array}\right.$

In formula: ω_jFor the weighted value after jth indicator combination；α, β are respectively subjective, the relatively important journey of objective weight Degree coefficient；g_js,g_jtIt is respectively s kind subjective weighting method and t kind objective weighted model and result is weighed in the tax of jth index；

6) use Lagrangian method solution procedure 5) model obtain:

${\mathrm{\ω}}_j=\frac{m(\mathrm{\α}\underset{s=1}{\overset{p}{\Σ}}{g}_{js}+\mathrm{\β}\underset{t=1}{\overset{k-p}{\Σ}}{g}_{jt})-\underset{j=1}{\overset{m}{\Σ}}(\mathrm{\α}\underset{s=1}{\overset{p}{\Σ}}{g}_{js}+\mathrm{\β}\underset{t=1}{\overset{k-p}{\Σ}}{g}_{jt})}{m\[\mathrm{\α}p+\mathrm{\β}(k-p)\]}+\frac{1}{m}$

Method for optimizing based on grey correlation analysis described in step S5, specifically includes following steps:

A. dimensionless process is carried out for n the scheme of candidate, m index of each scheme, obtain scheme set pair index Evaluations matrix x=(the x of collection_ij)_n×m；

B. x is made_opt=[x_opt1,x_opt2,…,x_optm] it is ideal scheme；In ideal scheme, the value rule of each index is:

If index is large index, then the maximum in corresponding index during each desired value takes each scheme in ideal scheme；

If index is minimal type index, then the minima in corresponding index during each desired value takes each scheme in ideal scheme；

C. the coefficient of association of the jth index calculating i-th scheme based on gray relative analysis method is used

D. by candidate scheme x_i={ x_i1,x_i2,…,x_imIt is expressed as a m dimension coordinate system { a_i1,a_i2,…,a_im}；Choose Space any point is as common origin, with ideal scheme x_optCorresponding desired value, as terminal, forms directed line segment oa_j, obtain Electric Power Network Planning ideal scheme directed line segment collection is { oa₁,oa₂,…,oa_m}；With candidate scheme x_iCorresponding desired value as terminal, Form directed line segment oa_ij, obtaining Electric Power Network Planning candidate scheme directed line segment collection is { oa_i1,oa_i2,…,oa_im}；And record oriented Line segment oa_jWith oa_ijAngle be θ_ij；

E. the coefficient of association cos of the jth index of computational methods based on cosine ranking method calculating i-th scheme is used θ_ij；

F. following formula is used to calculate the coefficient of association of jth index of i-th scheme:

${\mathrm{\ψ}}_{ij}={\mathrm{\ξ}}_j^i{\mathrm{cos\θ}}_{ij}$

G. calculating i-th candidate scheme and the degree of association of ideal scheme:

${\mathrm{\γ}}_i=\underset{j=1}{\overset{m}{\Σ}}{w}_j{\mathrm{\ψ}}_{ij}$

The degree of association of all candidate schemes H. obtained according to step G and ideal scheme is as evaluation index, with candidate side Case is the bigger the better as evaluation principle with the degree of association of ideal scheme, evaluates all candidate schemes.

The coefficient of association using the jth index calculating i-th scheme based on gray relative analysis method described in step CSpecially use the coefficient of association of the jth index of following formula calculating i-th scheme

${\mathrm{\ξ}}_j^i=\frac{\underset{i}{min}\underset{j}{min}|x_{optj}-x_{ij}|+\mathrm{\ρ}\underset{i}{\max }\underset{j}{\max }|x_{optj}-x_{ij}|}{|x_{optj}-x_{ij}|+\mathrm{\ρ}\underset{i}{\max }\underset{j}{\max }|x_{optj}-x_{ij}|}$

In formula, ρ is resolution ratio, takes 0.5.

The coefficient of association cos θ of the jth index of the calculating i-th scheme described in step E_ij, specially use following formula Calculate the coefficient of association cos θ of the jth index of i-th scheme_ij:

${\mathrm{cos\θ}}_{ij}=\frac{x_{ij}{x}_{optj}}{\sqrt{\underset{j=1}{\overset{m}{\Σ}}{x}_{ij}^2}\sqrt{\underset{j=1}{\overset{m}{\Σ}}{x}_{optj}^2}}$

The present invention is by setting up the evaluation index of distributing wind power group Optimal Transmission Expansion Planning scheme, according to each candidate scheme to electricity The impact of Force system, uses subjective weights method based on analytic hierarchy process (AHP) and Experts consultation method to calculate the subjectivity of each evaluation index Weight, Objective Weighting based on independent information data fluctuations method and entropy assessment calculates the objective weight of each evaluation index, base Determine that in the optimal weights combination method that moments estimation is theoretical grey correlation is divided by the weight of each evaluation index, creative proposing The improved Gray correlation fractal dimension that analysis method and cosine ranking method combine, carries out each Optimal Transmission Expansion Planning scheme preferably and obtains Optimal Optimal Transmission Expansion Planning scheme, therefore the present invention can evaluate each candidate scheme accurately, and methodological science, reliable, A set of analysis method brand-new, science is provided to the evaluation of distributing wind power group Optimal Transmission Expansion Planning scheme.

Accompanying drawing explanation

Fig. 1 is the assessment indicator system figure of the present invention.

Fig. 2 is the method flow diagram of the present invention.

Detailed description of the invention

It is illustrated in figure 2 the method flow diagram of the present invention: this distributing wind power group Optimal Transmission Expansion Planning side that the present invention provides The evaluation methodology of case, comprises the steps:

S1. distributing wind power group Optimal Transmission Expansion Planning scheme to be evaluated is obtained, and according to distributing wind power group Optimal Transmission Expansion Planning side The characteristic of case and power system obtains evaluation index；

Evaluation index includes economy, safety and three indexs of adaptability；Wherein economic index includes once investing With energy loss expense；Safety indexes includes that trend distribution, bus nodes voltage levvl, voltage stability, N-1 are checked, temporarily State stability check and the penetration limit；Adaptive criteria includes region electricity needs, sends reliability, enforcement difficulty, mistake Cross difficulty, development adaptability and near region dispatching of power netwoks to run.Assessment indicator system is concrete as shown in Figure 1.

S2. to distributing wind power group Optimal Transmission Expansion Planning scheme to be evaluated, use expert group that evaluation index is given a mark, obtain Decision matrix；

S3. for using subjective weights method based on analytic hierarchy process (AHP) and Experts consultation method to calculate the subjectivity of each evaluation index Weight, uses Objective Weighting based on independent information data fluctuations method and entropy assessment to calculate the objective power of each evaluation index Weight；

S4. use the optimum combination weight determining evaluation index based on the combination weighting method that moments estimation is theoretical, specifically walk Suddenly include:

1) from subjective weight totally p sample of extraction, objective weight totally in extracts k-p sample, and assume that m is individual The combining weights vector of evaluation index is W=[ω₁,ω₂,…,ω_m], wherein k and p is natural number, and k ＞ p；

2) for jth evaluation index, subjective weight g of following formula parameter is used_jsWith objective weight g_jtPhase Prestige value:

$\left\{\begin{array}{cc}E\left(g_{js}\right)=\frac{\underset{s=1}{\overset{p}{\Σ}}{g}_{js}}{p}& (1\≤s\≤p)\\ E\left(g_{jt}\right)=\frac{\underset{t=1}{\overset{k-p}{\Σ}}{g}_{jt}}{k-p}& (1\≤t\≤k-p)\end{array}\right.$

3) for jth index, its important coefficient subjective, objective is respectively as follows:

$\left\{\begin{array}{c}{\mathrm{\α}}_j=\frac{E\left(g_{js}\right)}{E\left(g_{js}\right)+E\left(g_{jt}\right)}\\ {\mathrm{\β}}_j=\frac{E\left(g_{jt}\right)}{E\left(g_{js}\right)+E\left(g_{jt}\right)}\end{array}\right.$

4) according to the following formula to main, objective important coefficient in aggregative indicator:

$\left\{\begin{array}{c}\mathrm{\α}=\frac{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\α}}_j}{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\α}}_j+\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\β}}_j}=\frac{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\α}}_j}{m}\\ \mathrm{\β}=\frac{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\β}}_j}{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\α}}_j+\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\β}}_j}=\frac{\underset{j=1}{\overset{m}{\Σ}}{\mathrm{\β}}_j}{m}\end{array}\right.$

5) comprehensive weight of each evaluation index in the seismic responses calculated comprehensive weight vector of following combining weights is used ω_j:

$\left\{\begin{array}{cc}\min & B=\underset{s=1}{\overset{p}{\Σ}}\underset{j=1}{\overset{m}{\Σ}}\mathrm{\α}{(g_{js}-{\mathrm{\ω}}_j)}^2+\underset{t=1}{\overset{k-p}{\Σ}}\underset{j=1}{\overset{m}{\Σ}}\mathrm{\β}{(g_{jt}-{\mathrm{\ω}}_j)}^2\\ s.t.& \underset{j=1}{\overset{m}{\Σ}}{\mathrm{\ω}}_j=1,0\≤{\mathrm{\ω}}_j\≤1\end{array}\right.$

In formula: ω_jFor the weighted value after jth indicator combination；α, β are respectively subjective, the relatively important journey of objective weight Degree coefficient；g_js,g_jtIt is respectively s kind subjective weighting method and t kind objective weighted model and result is weighed in the tax of jth index；

6) use Lagrangian method solution procedure 5) model obtain:

${\mathrm{\ω}}_j=\frac{m(\mathrm{\α}\underset{s=1}{\overset{p}{\Σ}}{g}_{js}+\mathrm{\β}\underset{t=1}{\overset{k-p}{\Σ}}{g}_{jt})-\underset{j=1}{\overset{m}{\Σ}}(\mathrm{\α}\underset{s=1}{\overset{p}{\Σ}}{g}_{js}+\mathrm{\β}\underset{t=1}{\overset{k-p}{\Σ}}{g}_{jt})}{m\[\mathrm{\α}p+\mathrm{\β}(k-p)\]}+\frac{1}{m}$

S5. the optimum combination weight obtained according to step S4, uses the method for optimizing side of carrying out based on grey correlation analysis Case is preferred, obtains optimal distributing wind power group Optimal Transmission Expansion Planning scheme, and concrete steps include:

A. dimensionless process is carried out for n the scheme of candidate, m index of each scheme, obtain scheme set pair index Evaluations matrix x=(the x of collection_ij)_n×m；

B. x is made_opt=[x_opt1,x_opt2,…,x_optm] it is ideal scheme；In ideal scheme, the value rule of each index is:

If index is large index, then the maximum in corresponding index during each desired value takes each scheme in ideal scheme；

If index is minimal type index, then the minima in corresponding index during each desired value takes each scheme in ideal scheme；

C. the coefficient of association of the jth index calculating i-th scheme based on gray relative analysis method is usedSpecific as follows Shown in formula:

${\mathrm{\ξ}}_j^i=\frac{\underset{i}{min}\underset{j}{min}|x_{optj}-x_{ij}|+\mathrm{\ρ}\underset{i}{\max }\underset{j}{\max }|x_{optj}-x_{ij}|}{|x_{optj}-x_{ij}|+\mathrm{\ρ}\underset{i}{\max }\underset{j}{\max }|x_{optj}-x_{ij}|}$

In formula, ρ is resolution ratio, takes 0.5；

D. by candidate scheme x_i={ x_i1,x_i2,…,x_imIt is expressed as a m dimension coordinate system { a_i1,a_i2,…,a_im}；Choose Space any point is as common origin, with ideal scheme x_optCorresponding desired value, as terminal, forms directed line segment oa_j, obtain Electric Power Network Planning ideal scheme directed line segment collection is { oa₁,oa₂,…,oa_m}；With candidate scheme x_iCorresponding desired value as terminal, Form directed line segment oa_ij, obtaining Electric Power Network Planning candidate scheme directed line segment collection is { oa_i1,oa_i2,…,oa_im}；And record oriented Line segment oa_jWith oa_ijAngle be θ_ij；

E. the coefficient of association cos of the jth index of computational methods based on cosine ranking method calculating i-th scheme is used θ_ij, shown in formula specific as follows:

${\mathrm{cos\θ}}_{ij}=\frac{x_{ij}{x}_{optj}}{\sqrt{\underset{j=1}{\overset{m}{\Σ}}{x}_{ij}^2}\sqrt{\underset{j=1}{\overset{m}{\Σ}}{x}_{optj}^2}}$

F. following formula is used to calculate the coefficient of association of jth index of i-th scheme:

${\mathrm{\ψ}}_{ij}={\mathrm{\ξ}}_j^i{\mathrm{cos\θ}}_{ij}$

G. calculating i-th candidate scheme and the degree of association of ideal scheme:

${\mathrm{\γ}}_i=\underset{j=1}{\overset{m}{\Σ}}{w}_j{\mathrm{\ψ}}_{ij}$

The degree of association of all candidate schemes H. obtained according to step G and ideal scheme is as evaluation index, with candidate side Case is the bigger the better as evaluation principle with the degree of association of ideal scheme, evaluates all candidate schemes.

Below in conjunction with a specific embodiment, the present invention is further described:

S1. determine all candidate scheme set, and set up the assessment indicator system of distributing wind power group Optimal Transmission Expansion Planning；

Assessment indicator system includes economy, safety and three first class index of adaptability.Economic index includes once Investment and two two-level index of energy loss expense；Safety indexes includes that trend distribution, bus nodes voltage levvl, voltage are steady Qualitative, N-1 checks, transient stability is checked and six two-level index such as the penetration limit；Adaptive criteria includes region electricity Power demand, send reliability, implement difficulty, transition difficulty, development adaptability and near region dispatching of power netwoks operation etc. six two grades Index；

S2: calculate the evaluation index value of each candidate scheme, is become judge group to refer to the evaluation of all candidate schemes by expert Mark marking, obtains decision matrix as shown in table 1 below:

Table 1 candidate scheme evaluation index marking table

S3: determine subjective weight set and the objective weight set of evaluation index；

Subjective weights method based on analytic hierarchy process (AHP) and Experts consultation method is used to calculate the subjective weight of each evaluation index It is respectively as follows:

W₁=[0.095,0.091,0.062,0.071,0.075,0.066,0.087,

0.079,0.083,0.058,0.083,0.054,0.050,0.046]

W₂=[0.097,0.093,0.086,0.080,0.076,0.070,0.074,

0.070,0.086,0.060,0.058,0.054,0.050,0.046]

Objective Weighting based on independent information data fluctuations method and entropy assessment is used to calculate the objective of each evaluation index Weight is:

W₃=[0.085,0.139,0.083,0.038,0.083,0.083,0.083,

0.083,0.042,0.038,0.055,0.052,0.052,0.086]

W₄=[0.081,0.079,0.077,0.081,0.077,0.077,0.077,

0.077,0.029,0.081,0.029,0.081,0.081,0.077]

S4: determine the optimum combination weight of evaluation index based on the combination weighting method that moments estimation is theoretical；

Try to achieve each index subjectivity and objective weight expected value set is respectively as follows:

$\begin{array}{c}{W}_{E_1}=\[0.096,0.092,0.074,0.075,0.075,0.068,0.080,\\ 0.075,0.085,0.059,0.070,0.054,0.050,0.046\]\end{array}$

$\begin{array}{c}{W}_{E_2}=\[0.083,0.109,0.080,0.059,0.080,0.080,0.080,\\ 0.080,0.036,0.059,0.042,0.067,0.067,0.081\]\end{array}$

Subjective and the objective important coefficient set trying to achieve each index is respectively as follows:

W_α=[0.538,0.458,0.483,0.559,0.486,0.462,0.503

0.484,0.704,0.499,0.627,0.448,0.428,0.360]

W_β=[0.462,0.542,0.517,0.441,0.514,0.538,0.497,

0.516,0.296,0.501,0.373,0.552,0.572,0.640]

Finally, try to achieve subjective and objective important coefficient to be respectively as follows:

α=0.503, β=0.497

Utilize Lagrangian method to solve, obtain composing based on moments estimation theory the optimum of each index that power method determines Combining weights is:

W=[0.090,0.101,0.077,0.067,0.077,0.074,0.080,

0.077,0.060,0.059,0.056,0.060,0.058,0.063]

S5: on the basis of oneself knows evaluation criterion weight, carries out scheme based on the grey correlation analysis method for optimizing improved Preferably；

Trying to achieve incidence coefficient matrix based on gray relative analysis method each scheme index with ideal scheme index is:

$\mathrm{\ξ}=\left[\begin{array}{cccccccccccccc}1& 0.6& 0.6& 0.6& 1& 0.43& 1& 0.43& 0.6& 1& 0.6& 1& 1& 0.43\\ 1& 1& 1& 1& 0.6& 0.6& 0.6& 1& 1& 1& 1& 1& 1& 0.6\\ 0.43& 0.33& 0.43& 1& 0.43& 1& 0.43& 0.6& 0.6& 0.6& 0.6& 0.6& 0.6& 1\end{array}\right]$

Trying to achieve incidence coefficient matrix based on cosine ranking method each scheme index with ideal scheme index is:

$\cos \mathrm{\θ}=\left[\begin{array}{cccccccccccccc}0.10& 0.07& 0.07& 0.07& 0.10& 0.05& 0.10& 0.05& 0.07& 0.10& 0.04& 0.06& 0.06& 0.02\\ 0.09& 0.09& 0.09& 0.09& 0.07& 0.07& 0.07& 0.09& 0.09& 0.09& 0.05& 0.05& 0.05& 0.03\\ 0.06& 0.03& 0.06& 0.12& 0.06& 0.12& 0.06& 0.09& 0.09& 0.09& 0.04& 0.04& 0.04& 0.07\end{array}\right]$

Trying to achieve incidence coefficient matrix based on the gray relative analysis method each scheme index improved with ideal scheme index is:

$\mathrm{\ψ}=\left[\begin{array}{cccccccccccccc}0.10& 0.04& 0.04& 0.04& 0.10& 0.02& 0.10& 0.04& 0.04& 0.10& 0.02& 0.06& 0.06& 0.01\\ 0.09& 0.09& 0.09& 0.09& 0.04& 0.04& 0.04& 0.09& 0.09& 0.09& 0.05& 0.05& 0.05& 0.02\\ 0.02& 0.01& 0.02& 0.12& 0.02& 0.12& 0.02& 0.05& 0.05& 0.05& 0.03& 0.03& 0.03& 0.07\end{array}\right]$

The optimum combination weight vectors being calculated each index is substituted into, calculates each decision scheme and optimum Optimal Transmission Expansion Planning The degree of association of scheme is:

P=[0.0522,0.0614,0.0387]

S6: recommendation distributing wind power group Optimal Transmission Expansion Planning preferred plan:

In general, the once investment of scheme two and energy loss expense are minimum, and safety and adaptability are all preferable, for Good scheme.

Claims (7)

1. an evaluation methodology for distributing wind power group Optimal Transmission Expansion Planning scheme, comprises the steps:

S1. obtain distributing wind power group Optimal Transmission Expansion Planning scheme to be evaluated, and according to distributing wind power group Optimal Transmission Expansion Planning scheme and The characteristic of power system obtains evaluation index；

S2. to distributing wind power group Optimal Transmission Expansion Planning scheme to be evaluated, use expert group that evaluation index is given a mark, obtain decision-making Matrix；

S3. subjective weight and the objective weight of each evaluation index are calculated；

S4. the optimum combination weight determining evaluation index based on the combination weighting method that moments estimation is theoretical is used；

S5. the optimum combination weight obtained according to step S4, uses method for optimizing based on grey correlation analysis to carry out scheme excellent Choosing, obtains optimal distributing wind power group Optimal Transmission Expansion Planning scheme.

The evaluation methodology of distributing wind power group Optimal Transmission Expansion Planning scheme the most according to claim 1, it is characterised in that step S1 Described evaluation index includes economy, safety and three indexs of adaptability；Wherein economic index include once investing and Energy loss expense；Safety indexes includes trend distribution, bus nodes voltage levvl, voltage stability, N-1 check, transient state Stability check and the penetration limit；Adaptive criteria includes region electricity needs, sends reliability, enforcement difficulty, transition Difficulty, development adaptability and near region dispatching of power netwoks run.

The evaluation methodology of distributing wind power group Optimal Transmission Expansion Planning scheme the most according to claim 1, it is characterised in that step S3 The subjective weight of described evaluation index and objective weight, for using based on analytic hierarchy process (AHP) and the subjective weights of Experts consultation method Method calculates the subjective weight of each evaluation index, uses based on independent information data fluctuations method and the Objective Weighting of entropy assessment Calculate the objective weight of each evaluation index.

The evaluation methodology of distributing wind power group Optimal Transmission Expansion Planning scheme the most according to claim 1, it is characterised in that step S4 The described combination weighting method theoretical based on moments estimation, concretely comprises the following steps:

1) from subjective weight totally p sample of extraction, objective weight totally in extract k-p sample, and assume that m is individual and comment The combining weights vector of valency index is W=[ω₁,ω₂,…,ω_m], wherein k and p is natural number, and k ＞ p；

2) for jth evaluation index, subjective weight g of following formula parameter is used_jsWith objective weight g_jtExpected value:

3) for jth index, its important coefficient subjective, objective is respectively as follows:

4) according to the following formula to main, objective important coefficient in aggregative indicator:

5) the comprehensive weight ω of each evaluation index in the seismic responses calculated comprehensive weight vector of following combining weights is used_j:

In formula: ω_jFor the weighted value after jth indicator combination；α, β are respectively subjective, the relative importance system of objective weight Number；g_js,g_jtIt is respectively s kind subjective weighting method and t kind objective weighted model and result is weighed in the tax of jth index；

6) use Lagrangian method solution procedure 5) model obtain:

。

5. according to the evaluation methodology of the distributing wind power group Optimal Transmission Expansion Planning scheme one of Claims 1 to 4 Suo Shu, it is characterised in that Method for optimizing based on grey correlation analysis described in step S5, specifically includes following steps:

A. dimensionless process is carried out for n the scheme of candidate, m index of each scheme, obtain scheme set pair index set Evaluations matrix x=(x_ij)_n×m；

B. x is made_opt=[x_opt1,x_opt2,…,x_optm] it is ideal scheme；In ideal scheme, the value rule of each index is:

If index is large index, then the maximum in corresponding index during each desired value takes each scheme in ideal scheme；

If index is minimal type index, then the minima in corresponding index during each desired value takes each scheme in ideal scheme；

C. the coefficient of association of the jth index calculating i-th scheme based on gray relative analysis method is used

D. by candidate scheme x_i={ x_i1,x_i2,…,x_imIt is expressed as a m dimension coordinate system { a_i1,a_i2,…,a_im}；Choose space to appoint A little as common origin, with ideal scheme x_optCorresponding desired value, as terminal, forms directed line segment oa_j, obtain electrical network Ideality of plan scheme directed line segment collection is { oa₁,oa₂,…,oa_m}；With candidate scheme x_iCorresponding desired value, as terminal, is formed Directed line segment oa_ij, obtaining Electric Power Network Planning candidate scheme directed line segment collection is { oa_i1,oa_i2,…,oa_im}；And record directed line segment oa_jWith oa_ijAngle be θ_ij；

E. the coefficient of association cos θ of the jth index of computational methods based on cosine ranking method calculating i-th scheme is used_ij；

F. following formula is used to calculate the coefficient of association of jth index of i-th scheme:

G. calculating i-th candidate scheme and the degree of association of ideal scheme:

The degree of association of all candidate schemes H. obtained according to step G and ideal scheme as evaluation index, with candidate scheme with The degree of association of ideal scheme is the bigger the better as evaluation principle, evaluates all candidate schemes.

The evaluation methodology of distributing wind power group Optimal Transmission Expansion Planning scheme the most according to claim 5, it is characterised in that step C institute The coefficient of association using the jth index calculating i-th scheme based on gray relative analysis method statedIt is specially employing as follows Formula calculates the coefficient of association of the jth index of i-th scheme

In formula, ρ is resolution ratio, takes 0.5.

The evaluation methodology of distributing wind power group Optimal Transmission Expansion Planning scheme the most according to claim 5, it is characterised in that step E institute The coefficient of association cos θ of the jth index of the calculating i-th scheme stated_ij, specially use following formula to calculate i-th scheme The coefficient of association cos θ of jth index_ij:

。