CN104392397A - Entropy weight method based short-circuit current suppression scheme evaluation method - Google Patents

Abstract

The invention relates to an entropy weight method based short-circuit current suppression scheme evaluation method. The method comprises calculating weights of all current-limiting effect indexes in a power grid short-circuit current suppression scheme through an entropy weight method, establishing an index evaluation matrix according to the indexes, and calculating weights of the indexes after performing standardization processing on the evaluation indexes. By means of the index weight calculation, effects of subjective factors can be prevented effectively, and results are objective and accurate. After index weights are determined through the entropy weight method, evaluation of the power grid short-circuit current suppression scheme is achieved through a distance synthesis method, and the calculated relative proximities of the schemes are sorted for scheme prioritizing. According to the method, the relative significance degree of different current limit effect indexes is considered in a weight mode, the scheme current limit effect is analyzed comprehensively from a plurality of angles, the indexes of different natures and different dimensions in the power grid short-circuit current suppression scheme are synthesized into relative proximity indexes, and evaluation of the power grid short-circuit current suppression scheme is achieved according to values of the indexes.

Description

Entropy weight method-based short circuit current suppression scheme evaluation method

Technical Field

The invention relates to an evaluation method in the field of power systems, in particular to an entropy weight method-based evaluation method for a short-circuit current suppression scheme.

Background

With the continuous expansion of power grid planning, grid structures are more and more compact, the level of short-circuit current is further increased, the problem that the level of short-circuit current of some urban power grids exceeds standard is increasingly prominent, and the limitation of the level of short-circuit current of the power grids becomes a problem to be solved urgently. At present, measures for limiting the level of short-circuit current mainly include bus sectionalized operation of a transformer substation, partitioned operation of a power grid, adoption of a high-impedance transformer and a line or bus-coupled series impedance and the like. Different short-circuit current limiting measures have different influences on system safety, economic operation and the like while reducing the level of short-circuit current. At present, a short-circuit current limiting method generally selects current limiting measures by experience, compares and analyzes the short-circuit current, the current and the stability level of a power grid after the measures are taken, and finally works out one or more short-circuit current limiting schemes. The traditional method for making the current limiting scheme is difficult to realize comprehensive, comprehensive and objective evaluation on the current limiting scheme. In order to evaluate the short-circuit current limiting measures more effectively and provide a technical basis for selecting an optimal scheme, the invention provides an entropy weight method-based short-circuit current suppression scheme evaluation method.

Entropy is a measure of the degree of disorder of the system, which measures the amount of useful information provided by the data. When the weight is determined by using entropy, when the value difference of an evaluation object on a certain index is large, the entropy value is small, which indicates that the effective information provided by the index is large, and the weight of the index is also large; on the contrary, if the difference between the values of a certain index is small and the entropy value is large, it indicates that the amount of information provided by the index is small and the weight of the index is small. Meanwhile, the distance synthesis method can determine the distance from each evaluation object to the reference point by using the index weight obtained by calculation, so that the comprehensive evaluation of each research object can be realized. The short-circuit current suppression scheme evaluation by using the distance synthesis method can fully utilize the known index information, improve the reliability of the comprehensive effect of the short-circuit current suppression scheme and provide a technical basis for scheme selection.

Disclosure of Invention

Aiming at the defects of the prior art, the invention aims to provide an entropy weight method-based short-circuit current suppression scheme evaluation method, which comprehensively considers the current limiting effect of various short-circuit current suppression measures, the influence on the power grid safety, the economic cost and other factors, calculates each evaluation index weight by using the entropy weight method, evaluates the 220kV power grid short-circuit current suppression scheme through distance comprehensive analysis, and determines the optimal scheme according to the calculated sequencing of the relative closeness of each scheme.

The purpose of the invention is realized by adopting the following technical scheme:

the invention provides a short-circuit current suppression scheme evaluation method based on an entropy weight method, which is improved in that the method comprises the following steps:

(1) determining an evaluation index of a short-circuit current suppression scheme;

(2) establishing an evaluation matrix, and determining an index weight by using an entropy weight method;

(3) and analyzing the relative proximity of the current limiting scheme, and realizing the evaluation of the power grid short-circuit current suppression scheme by using a distance synthesis method.

Further, the evaluation index in the step (1) includes:

1) short circuit current level index:

the short-circuit current level index is calculated by combining the three-phase short-circuit current level and the single-phase short-circuit current level of the 220kV power grid and calculating by using the bus short-circuit current larger than 47kA, and the short-circuit current level index alpha is_shortThe calculation was performed using the following formula:

<math> <mrow> <msub> <mi>&alpha;</mi> <mi>short</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>p</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mo>|</mo> <msub> <mi>I</mi> <mn>47</mn> </msub> <mo>/</mo> <msub> <mi>I</mi> <mn>0</mn> </msub> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>1</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula I₄₇In order to adopt the bus short-circuit current larger than 47kA after the current limiting measure, m is the number of buses, I₀Rated breaking current for the circuit breaker of the corresponding substation;

2) main transformer load factor:

the calculation of the load rate index of the main transformer is combined with the main load rate of the 500kV station, and the main load rate of the main transformer is more than 60 percent; the main transformer load factor index beta is calculated by adopting the following formula:

<math> <mrow> <mi>&beta;</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>q</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mo>|</mo> <mi>S</mi> <mo>/</mo> <msub> <mi>S</mi> <mi>N</mi> </msub> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>2</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula, S is the main transformer load capacity with the main transformer load rate of more than 60 percent after the current limiting measure is taken, n is the number of main transformers, and S_NThe rated capacity of the main transformer is obtained;

3) and (3) system static safety indexes:

by using bus voltage out-of-limit index gamma_VAnd line overload indicator gamma_LCalculating the system static safety index gamma:

γ＝γ_V+γ_L <3>；

by the formula<4>Calculating out-of-limit index gamma of bus voltage_V：

<math> <mrow> <msub> <mi>&gamma;</mi> <mi>V</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mo>|</mo> <mfrac> <mrow> <msub> <mi>U</mi> <mi>i</mi> </msub> <mo>-</mo> <mrow> <mo>(</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>H</mi> </msubsup> <mo>+</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>L</mi> </msubsup> <mo>)</mo> </mrow> <mo>/</mo> <mn>2</mn> </mrow> <mrow> <mrow> <mo>(</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>H</mi> </msubsup> <mo>-</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>L</mi> </msubsup> <mo>)</mo> </mrow> <mo>/</mo> <mn>2</mn> </mrow> </mfrac> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>4</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

Wherein m is the number of buses, U_iIs the voltage amplitude of the bus i,andthe upper and lower limit values of the voltage amplitude of the bus i are respectively;

by the formula<5>Calculating line overload index gamma_L：

<math> <mrow> <msub> <mi>&gamma;</mi> <mi>L</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mo>|</mo> <mfrac> <msub> <mi>S</mi> <mi>j</mi> </msub> <msub> <mi>S</mi> <mi>je</mi> </msub> </mfrac> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>5</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

Where n is the set of lines, S_iIs the actual transmission power of line i, S_ieIs the allowed transmission power of line i;

4) calculating the transient stability index of the system of the maximum power angle difference of the generator by using the following formula <6 >:

_max＝max|_i-_j| <6>；

wherein,_iand_jthe power angles of any two generators in the transient process after the fault is removed;

5) the economic index is as follows:

the economic indexes of the current-limiting scheme comprise direct investment cost and indirect investment cost of the adopted measures and system operation network loss cost; the direct investment cost comprises the investment increased by adopting a high-impedance transformer and a series reactor device, and the indirect investment cost comprises the cost related to engineering construction;

by the formula<7>Calculating an economic indicator E_loss：

E_loss＝M_invd+M_invind+M_Ploss <7>；

Wherein M is_invdRepresents a direct investment cost; m_invindRepresents an indirect investment cost; m_PlossRepresenting increased network loss costs.

Further, the step (2) comprises the steps of:

setting an evaluation matrix of evaluation indexes of a short-circuit current suppression scheme;

standardizing the original evaluation indexes;

defining the entropy of the evaluation index;

and fourthly, defining an evaluation index entropy weight.

Further, the step (i) includes: let the evaluation index vector of j short-circuit current suppression schemes be X_j＝[x_1j,x_2j,x_3j,x_4j,x_5j]^TWherein x is_1jThree-phase short-circuit current, x, of bus of 220kV power grid_2jIs the main variable load rate, x_3jFor bus voltage out-of-limit and line overload indicators, x_4jIs the maximum power angle difference, x, between two generators_5jIs an economic index;

if there are n short-circuit current suppression schemes, thenThe evaluation matrix is expressed as X ═ X₁,X₂,…,X_n](ii) a The weight of the short-circuit current suppression scheme evaluation index is represented by ω, and the weight vector is ω ═ ω₁,ω₂,...,ω_i]^Ti is 5; wherein i represents an evaluation index number;

the expression X ═ X (X) for establishing the evaluation matrix_ij)_m×nWhere m is the number of evaluation indexes and n is the number of objects to be evaluated.

Further, the step (ii) includes: if the m evaluation indexes have negative indexes, namely indexes with smaller index values and better conditions are represented, firstly carrying out index homologization processing, converting the indexes into positive indexes and carrying out unified processing, wherein the positive indexes have better conditions reflected when the index values are larger;

carrying out standardization processing on the original evaluation matrix by adopting an equation (9) and an equation (10), converting a negative index into a positive index and normalizing all indexes; the raw evaluation matrix is normalized to obtain:

R＝(r_ij)_m×n <8>；

in the formula, r_ijA standard value, r, representing the jth evaluation object on the ith evaluation index_ij∈[0,1]；

For the forward direction index, the normalization process is as follows:

$r_{\mathrm{ij}}=\frac{x_{\mathrm{ij}}-\min \left\{x_{\mathrm{ij}}\right\}}{\max \left\{x_{\mathrm{ij}}\right\}-\min \left\{x_{\mathrm{ij}}\right\}}---<9>;$

for the negative indicators, the normalization process is:

$r_{\mathrm{ij}}=\frac{\max \left\{x_{\mathrm{ij}}\right\}-x_{\mathrm{ij}}}{\max \left\{x_{\mathrm{ij}}\right\}-\min \left\{x_{\mathrm{ij}}\right\}}---<10>;$

wherein r is_ijElements of the standard evaluation matrix.

Further, the third step includes: in the evaluation problem with m evaluation indexes and n evaluation objects, the entropy H of the ith index_iIs defined as:

<math> <mrow> <msub> <mi>H</mi> <mi>i</mi> </msub> <mo>=</mo> <mo>-</mo> <mi>k</mi> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>f</mi> <mi>ij</mi> </msub> <mi>ln</mi> <msub> <mi>f</mi> <mi>ij</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>m</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>11</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula:k is 1/lnn, when f_ijWhen equal to 0, let f_ijlnf_ij＝0；f_ijRepresents a normalized value; k denotes an adjustment coefficient.

Further, in the step (iv), the entropy weight w of the ith index_iIs defined as:

<math> <mrow> <msub> <mi>w</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mn>1</mn> <mo>-</mo> <msub> <mi>H</mi> <mi>i</mi> </msub> </mrow> <mrow> <mi>m</mi> <mo>-</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>H</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>12</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula, w is more than or equal to 0_i≤1，

Further, the step (3) comprises the steps of:

B. calculating the distance from the sample point to the reference point;

B. the relative proximity is calculated.

Further, in the step A, the weight determined by the entropy weight method is according to the formula<13>Determining a weighted data matrix Z ═ Z_ij]_m×n：

Z＝R·ω <13>；

Wherein: r represents the normalized evaluation matrix; omega represents an entropy weight;

the evaluation indexes are normalized, the maximum value of each index in all samples is used for forming an ideal sample, the minimum value of each index is used for forming a negative ideal sample, and Z is used respectively⁺And Z^-Represents;

defining the distance from the sample point to the optimal point as D +, which is calculated as shown in equation <14 >:

<math> <mrow> <msubsup> <mi>D</mi> <mi>j</mi> <mo>+</mo> </msubsup> <mo>=</mo> <msqrt> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>ij</mi> </msub> <mo>-</mo> <msubsup> <mi>z</mi> <mi>j</mi> <mo>+</mo> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </msqrt> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>n</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>14</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

defining the distance from the sample point to the worst point as D-, which is calculated as shown in equation <15 >:

<math> <mrow> <msubsup> <mi>D</mi> <mi>j</mi> <mo>-</mo> </msubsup> <mo>=</mo> <msqrt> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>ij</mi> </msub> <mo>-</mo> <msubsup> <mi>z</mi> <mi>j</mi> <mo>-</mo> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </msqrt> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>n</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>15</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

wherein: z is a radical of_ijRepresenting elements in a weighted data matrix Z;an ideal sample representing the ith index;representing a negative ideal sample of the ith index.

Further, in the step B, the relative proximity is calculated by the formula <16 >:

$C_j=\frac{D_j^{-}}{D_j^{-}+D_j^{+}}---<16>;$

according to relative proximity C_jThe size of (2), sorting each evaluation object; c_jThe larger the distance between the evaluation object and the ideal sample, the better the evaluation result of the evaluation object.

Compared with the closest prior art, the invention has the following beneficial effects:

(1) and (4) calculating the weight of each current limiting effect index in the power grid short-circuit current suppression scheme by adopting an entropy weight method. The method comprises the steps of firstly establishing an index evaluation matrix according to each index, and calculating the weight of each index after carrying out standardization processing on each evaluation index. The index weight calculation can effectively avoid the influence of subjective factors, and the result is more objective and accurate.

(2) After the index weight is determined by adopting an entropy weight method, the evaluation of the power grid short-circuit current suppression scheme is further realized by adopting a distance synthesis method, and scheme optimization is carried out by sequencing the relative closeness of each calculated scheme. The method can fully utilize the known current limiting effect index information and can further improve the reliability of the comprehensive effect of the current limiting scheme.

The evaluation method of the short-circuit current suppression scheme considers the relative importance degree of different current-limiting effect indexes in the form of weight, comprehensively analyzes the current-limiting effect of the scheme from multiple angles, integrates the indexes with different properties and different dimensions in the power grid short-circuit current suppression scheme into a relative proximity index, and realizes the evaluation of the power grid short-circuit current suppression scheme according to the index value.

Drawings

Fig. 1 is a flow chart of a short-circuit current suppression scheme evaluation method in an entropy weight method and a distance synthesis method provided by the invention.

Detailed Description

The following describes embodiments of the present invention in further detail with reference to the accompanying drawings.

The invention provides a short-circuit current suppression scheme evaluation method based on an entropy weight method, which adopts the entropy weight method to calculate the effect index weight of each short-circuit current suppression scheme, obtains the relative proximity of each scheme performance index sample to an optimal index sample through the calculation of a distance synthesis method, and realizes the evaluation of the comprehensive effect of the short-circuit current suppression scheme of a 220kV power grid and the preferential selection of the scheme through sequencing the relative proximity obtained through calculation. The flow chart of the method is shown in fig. 1, and comprises the following steps:

(1) effect index of short circuit current suppression scheme

The measures which can be taken for limiting the short-circuit current level of the power grid mainly consider the power grid subarea operation, the bus separation, the line series impedance, the adoption of a high-impedance transformer, the installation of a small reactance at the neutral point of the transformer and the like, and each current limiting scheme adopts the power grid subarea operation and is combined with one or more other measures. And if only the power grid partitioning measures are adopted to meet the requirements that the short-circuit current level does not exceed the standard and the like, only the measures are adopted. The current limiting scheme evaluation mainly considers indexes such as three-phase short-circuit current level suppression effect, main transformer load rate, system static safety (including bus voltage out-of-limit and line overload conditions), system transient stability (mainly considering maximum power angle difference of a generator), economy and the like, and all the index values are obtained through an expert scoring mechanism or according to actual values.

The current limiting effect index of the short-circuit current suppression scheme is calculated as follows:

1) short circuit current level index

The calculation of the index is mainThe three-phase short-circuit current level and the single-phase short-circuit current level of the 220kV bus are considered, and the bus short-circuit current larger than 47kA is adopted for calculation. Short circuit current level index alpha_shortThe calculation was performed using the following formula:

<math> <mrow> <msub> <mi>&alpha;</mi> <mi>short</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>p</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mo>|</mo> <msub> <mi>I</mi> <mn>47</mn> </msub> <mo>/</mo> <msub> <mi>I</mi> <mn>0</mn> </msub> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>1</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula I₄₇In order to adopt the bus short-circuit current larger than 47kA after the current limiting measure, m is the number of buses, I₀Rated breaking current for the circuit breaker of the corresponding substation.

2) Main change load factor

The index is calculated by mainly considering the main variable load rate of the 500kV station and adopting the main variable load rate of more than 60 percent. The main transformer load factor index beta is calculated by adopting the following formula:

<math> <mrow> <mi>&beta;</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>q</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mo>|</mo> <mi>S</mi> <mo>/</mo> <msub> <mi>S</mi> <mi>N</mi> </msub> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>2</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula, S is a main transformer with the load rate of the main transformer being more than 60 percent after a current limiting measure is takenLoad capacity, n is the number of main transformers, S_NThe rated capacity of the main transformer is obtained.

3) Static safety index of system

As shown in<3>It shows that the static safety index mu of the system utilizes the bus voltage out-of-limit index mu_VAnd line overload indicator mu_LAnd calculating to obtain:

γ＝γ_V+γ_L <3>

bus voltage out-of-limit index mu_UIs calculated as<4>Shown in the figure:

<math> <mrow> <msub> <mi>&gamma;</mi> <mi>V</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mo>|</mo> <mfrac> <mrow> <msub> <mi>U</mi> <mi>i</mi> </msub> <mo>-</mo> <mrow> <mo>(</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>H</mi> </msubsup> <mo>+</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>L</mi> </msubsup> <mo>)</mo> </mrow> <mo>/</mo> <mn>2</mn> </mrow> <mrow> <mrow> <mo>(</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>H</mi> </msubsup> <mo>-</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>L</mi> </msubsup> <mo>)</mo> </mrow> <mo>/</mo> <mn>2</mn> </mrow> </mfrac> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>4</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formulaM is the number of bus lines, U_iIs the voltage amplitude, U, of the bus i_i ^HAnd U_i ^LRespectively, the upper and lower limit values.

The calculation of the line overload index is shown as the formula <5 >:

<math> <mrow> <msub> <mi>&gamma;</mi> <mi>L</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mo>|</mo> <mfrac> <msub> <mi>S</mi> <mi>j</mi> </msub> <msub> <mi>S</mi> <mi>je</mi> </msub> </mfrac> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>5</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

where n is the set of lines, S_jIs the actual transmission power, S, of line j_jeIs the allowed transmission power of line j.

4) System transient stability index (Generator maximum power angle difference)

_max＝max|_a-_b| <6>

In the formula,_aand_bthe power angles of any two generators in the transient process after the fault is removed.

5) Index of economic efficiency

The economic indicators of the current-limiting scheme are mainly the direct and indirect investment costs of the measures taken and the system operation network loss costs. The direct investment is mainly the investment increased by adopting equipment such as a high-impedance transformer, a series reactor and the like, and the indirect investment mainly comprises the related expenses such as engineering construction and the like.

Economic index E_lossIs calculated as<7>Shown in the figure:

E_loss＝M_invd+M_invind+M_Ploss <7>

in the formula, M_invdRepresents a direct investment cost; m_invindRepresents an indirect investment cost; m_PlossRepresenting increased network loss costs.

(2) Evaluation matrix establishment and index weight calculation

Constructing an evaluation matrix according to each index of the short-circuit current suppression scheme, determining the weight of each index by using an entropy weight method, and mainly calculating the following steps:

1) establishing an evaluation matrix

The number of evaluation indexes of each short-circuit current suppression scheme is 5, and the evaluation index vector of the jth short-circuit current suppression scheme is X_j＝[x_1j,x_2j,x_3j,x_4j,x_5j]^TWherein x is_1jThree-phase short-circuit current, x, of bus of 220kV power grid_2jIs the main variable load rate, x_3jFor bus voltage out-of-limit and line overload indicators, x_4jIs the maximum power angle difference, x, between two generators_5jIs an economic index.

If there are n short-circuit current suppression schemes, the evaluation matrix may be represented as X ═ X₁,X₂,…,X_n]. The weight of the short-circuit current suppression scheme evaluation index is represented by ω, and the weight vector is ω ═ ω₁,ω₂,...,ω_i]^Ti-5. Wherein i represents an evaluation index number.

The evaluation matrix X ═ X (X) can be established according to the construction method described above_ij)_m×nWhere m is the number of evaluation indexes and n is the number of objects to be evaluated.

2) Normalization of raw evaluation matrices

If the m evaluation indexes have negative indexes, namely indexes with better conditions are represented by smaller index values, the indexes need to be subjected to index homonymization firstly, the indexes are converted into positive indexes to be subjected to unified processing, and the conditions reflected by the positive indexes are better when the positive indexes represent larger index values.

The original evaluation matrix is normalized by using the formula <9> and the formula <10>, the negative indicators are converted into the positive indicators, and all the indicators are normalized. The raw evaluation matrix is normalized to obtain:

R＝(r_ij)_m×n <8>

in the formula, r_ij-the standard value, r, of the jth evaluation object on the ith evaluation index_ij∈[0,1]。

For the forward direction index, the normalization process is as follows:

$r_{\mathrm{ij}}=\frac{x_{\mathrm{ij}}-\min \left\{x_{\mathrm{ij}}\right\}}{\max \left\{x_{\mathrm{ij}}\right\}-\min \left\{x_{\mathrm{ij}}\right\}}---<9>;$

for the negative indicators, the normalization process is:

$r_{\mathrm{ij}}=\frac{\max \left\{x_{\mathrm{ij}}\right\}-x_{\mathrm{ij}}}{\max \left\{x_{\mathrm{ij}}\right\}-\min \left\{x_{\mathrm{ij}}\right\}}---<10>;$

wherein r is_ijElements of the standard evaluation matrix.

3) Definition entropy

In an evaluation problem with m indexes and n evaluation objects, the entropy of the ith index is defined as:

<math> <mrow> <msub> <mi>H</mi> <mi>i</mi> </msub> <mo>=</mo> <mo>-</mo> <mi>k</mi> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>f</mi> <mi>ij</mi> </msub> <mi>ln</mi> <msub> <mi>f</mi> <mi>ij</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>m</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>11</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formulak is 1/lnn, when f_ijWhen equal to 0, let f_ijlnf_ij＝0；f_ijRepresents a normalized value; k denotes an adjustment coefficient.

4) Defining entropy weights

After the entropy of the ith index is defined, the entropy weight of the ith index is defined as:

<math> <mrow> <msub> <mi>w</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mn>1</mn> <mo>-</mo> <msub> <mi>H</mi> <mi>i</mi> </msub> </mrow> <mrow> <mi>m</mi> <mo>-</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>H</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>12</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula, w is more than or equal to 0_i≤1，

(3) Relative proximity of current limiting schemes

The distance synthesis method adopts relative proximity to represent the distance between each evaluation object and a reference point. Firstly, determining reference points in space, including optimal and worst points, and then calculating the distance between each evaluation object and the reference points, wherein the closer to the optimal point or the farther from the worst point indicates the better comprehensive characteristics of the evaluated object. The specific calculation is as follows:

1) distance calculation of sample points to reference points

Using the weights determined by the entropy weight method, a weighted data matrix Z can be determined according to equation <13 >.

Z＝R·ω <13>

Because the indexes are already forward, the maximum value of each index in all samples can be used for forming an ideal sample, the minimum value of each index can be used for forming a negative ideal sample, and Z is used for forming a negative ideal sample⁺And Z^-And (4) showing.

Defining the distance of the sample point to the optimal point as D +, which is calculated by the equation <14 >:

<math> <mrow> <msubsup> <mi>D</mi> <mi>j</mi> <mo>+</mo> </msubsup> <mo>=</mo> <msqrt> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>ij</mi> </msub> <mo>-</mo> <msubsup> <mi>z</mi> <mi>j</mi> <mo>+</mo> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </msqrt> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>n</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>14</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

defining the distance from the sample point to the worst point as D-, which is calculated by the equation <15 >:

<math> <mrow> <msubsup> <mi>D</mi> <mi>j</mi> <mo>-</mo> </msubsup> <mo>=</mo> <msqrt> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>ij</mi> </msub> <mo>-</mo> <msubsup> <mi>z</mi> <mi>j</mi> <mo>-</mo> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </msqrt> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>n</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>15</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

wherein: z is a radical ofⁱ _jRepresenting elements in a weighted data matrix Z;an ideal sample representing the ith index;representing a negative ideal sample of the ith index.

2) Relative proximity calculation

The relative proximity is calculated by the equation <16 >:

$C_j=\frac{D_j^{-}}{D_j^{-}+D_j^{+}}---<16>;$

according to relative proximity C_jThe evaluation objects may be sorted according to the size of (2). C_jThe larger the evaluation result, the smaller the relative distance between the evaluation object and the ideal sample, and the better the evaluation result of the corresponding evaluation object.

Examples

The technical scheme of the invention mainly comprises two parts, namely, the effect index weight of the short-circuit current limiting measure is determined by using an entropy weight method, and the short-circuit current suppression scheme is evaluated by using a distance synthesis method.

Next, a specific embodiment of the proposed short-circuit current suppression scheme evaluation method will be described with reference to the algorithm application flowchart 1.

(1) Constructing an evaluation matrix by using the short-circuit current suppression effect indexes of each scheme;

(2) carrying out standardization processing on the evaluation matrix to further obtain a standard matrix;

(3) calculating the weight of each current-limiting index by using an entropy weight method;

(4) calculating the relative proximity of the short-circuit current suppression scheme by using a distance integration method to realize the evaluation of the short-circuit current suppression scheme;

(5) and sequencing the relative closeness of the calculated schemes to realize the preference of the short-circuit current suppression scheme.

Assuming that there are n current limiting schemes, the current limiting effect index values of each scheme are shown in table 1:

TABLE 1 short-circuit current suppression Effect index for different schemes

The comprehensive effect of the short-circuit current suppression scheme is evaluated by the following steps:

step 1: according to the entropy weight method, an evaluation matrix R is generated by using the evaluation indexes of each scheme:

step 2: and carrying out de-standardization processing on the obtained matrix elements to obtain a standard matrix R':

in the formula, <math> <mrow> <msubsup> <mi>r</mi> <mi>ij</mi> <mrow> <mo>&prime;</mo> <mo>&prime;</mo> </mrow> </msubsup> <mo>=</mo> <mfrac> <mrow> <mi>max</mi> <mo>{</mo> <msub> <mi>r</mi> <mi>ij</mi> </msub> <mo>}</mo> <mo>-</mo> <msub> <mi>r</mi> <mi>ij</mi> </msub> </mrow> <mrow> <mi>max</mi> <mo>{</mo> <msub> <mi>r</mi> <mi>ij</mi> </msub> <mo>}</mo> <mo>-</mo> <mi>min</mi> <mo>{</mo> <msub> <mi>r</mi> <mi>ij</mi> </msub> <mo>}</mo> </mrow> </mfrac> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mn>5</mn> <mo>.</mo> </mrow> </math>

step 3: calculating the entropy H of the ith index in the index matrix_i：

<math> <mrow> <msub> <mi>H</mi> <mi>i</mi> </msub> <mo>=</mo> <mo>-</mo> <mi>k</mi> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>f</mi> <mi>ij</mi> </msub> <mi>ln</mi> <msub> <mi>f</mi> <mi>ij</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mn>5</mn> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>19</mn> <mo>></mo> </mrow> </math>

Step 4: entropy H of utilization index_iCalculating the weight w of the ith index_i：i＝1,2,…,5。

Step 5: and generating a normalized matrix Z by using each index of the short-circuit current suppression scheme.

Step 6: using sample point to optimum point distance D⁺And distance D of worst point^－Calculating the relative proximity C_j。

Step 7: according to relative proximity C_jThe evaluation of the comprehensive effects of different short-circuit current suppression schemes is realized, and the relative proximity C is evaluated_jThe sequencing result can provide guidance for selecting a scheme with the optimal comprehensive effect of short-circuit current suppression.

The invention provides a power grid short circuit current suppression effect index weight calculation method based on an entropy weight method. The method mainly comprises the steps of establishing an evaluation matrix by utilizing each current-limiting effect index, carrying out standardization processing on the evaluation indexes, and calculating the weight of each current-limiting effect index in a scheme, thereby determining the relative importance degree of each index. The invention also discloses an evaluation method for realizing the power grid short-circuit current suppression scheme by adopting the distance synthesis method, and the adopted distance synthesis method directly utilizes the internal relation of the given scheme indexes to evaluate each scheme, so that the subjectivity and uncertainty caused by the determination of the evaluation standard can be effectively avoided. According to the method, the importance degrees of different indexes, namely the index weights, are considered, indexes with different properties and different dimensions in the power grid short-circuit current suppression scheme are synthesized into one index, and the effect of the current limiting scheme is comprehensively analyzed from different angles. And finally, sequencing the relative closeness of each calculated scheme to realize the evaluation preference of the power grid short-circuit current suppression scheme.

Finally, it should be noted that: although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can make modifications and equivalents to the embodiments of the present invention without departing from the spirit and scope of the present invention, which is set forth in the claims of the present application.

Claims (10)

1. An entropy weight method-based short circuit current suppression scheme evaluation method is characterized by comprising the following steps of:

(1) determining an evaluation index of a short-circuit current suppression scheme;

(2) establishing an evaluation matrix, and determining an index weight by using an entropy weight method;

(3) and analyzing the relative proximity of the current limiting scheme, and realizing the evaluation of the power grid short-circuit current suppression scheme by using a distance synthesis method.

2. The short-circuit current suppression scheme evaluation method according to claim 1, wherein the evaluation index in step (1) includes:

1) short circuit current level index:

the short-circuit current level index is calculated by combining the three-phase short-circuit current level and the single-phase short-circuit current level of the 220kV power grid and calculating by using the bus short-circuit current larger than 47kA, and the short-circuit current level index alpha is_shortThe calculation was performed using the following formula:

<math> <mrow> <msub> <mi>&alpha;</mi> <mi>short</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>p</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mo>|</mo> <msub> <mi>I</mi> <mn>47</mn> </msub> <mo>/</mo> <msub> <mi>I</mi> <mn>0</mn> </msub> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>1</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula I₄₇In order to adopt the bus short-circuit current larger than 47kA after the current limiting measure, m is the number of buses, I₀Rated breaking current for the circuit breaker of the corresponding substation;

2) main transformer load factor:

the calculation of the load rate index of the main transformer is combined with the main load rate of the 500kV station, and the main load rate of the main transformer is more than 60 percent; the main transformer load factor index beta is calculated by adopting the following formula:

<math> <mrow> <mi>&beta;</mi> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>q</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mo>|</mo> <mi>S</mi> <mo>/</mo> <msub> <mi>S</mi> <mi>N</mi> </msub> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>2</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula, S is the main transformer load capacity with the main transformer load rate of more than 60 percent after the current limiting measure is taken, n is the number of main transformers, and S_NThe rated capacity of the main transformer is obtained;

3) and (3) system static safety indexes:

by using bus voltage out-of-limit index gamma_VAnd line overload indicator gamma_LCalculating the system static safety index gamma:

γ＝γ_V+γ_L <3>；

by the formula<4>Calculating out-of-limit index gamma of bus voltage_V：

<math> <mrow> <msub> <mi>&gamma;</mi> <mi>V</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <mo>|</mo> <mfrac> <mrow> <msub> <mi>U</mi> <mi>i</mi> </msub> <mo>-</mo> <mrow> <mo>(</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>H</mi> </msubsup> <mo>+</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>L</mi> </msubsup> <mo>)</mo> </mrow> <mo>/</mo> <mn>2</mn> </mrow> <mrow> <mrow> <mo>(</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>H</mi> </msubsup> <mo>-</mo> <msubsup> <mi>U</mi> <mi>i</mi> <mi>L</mi> </msubsup> <mo>)</mo> </mrow> <mo>/</mo> <mn>2</mn> </mrow> </mfrac> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>4</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

Wherein m is the number of buses, U_iElectricity being bus iThe magnitude of the pressure is such that,andthe upper and lower limit values of the voltage amplitude of the bus i are respectively;

by the formula<5>Calculating line overload index gamma_L：

<math> <mrow> <msub> <mi>&gamma;</mi> <mi>L</mi> </msub> <mo>=</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <mo>|</mo> <mfrac> <msub> <mi>S</mi> <mi>j</mi> </msub> <msub> <mi>S</mi> <mi>je</mi> </msub> </mfrac> <mo>|</mo> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>5</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

Where n is the set of lines, S_iIs the actual transmission power of line i, S_ieIs the allowed transmission power of line i;

4) calculating the transient stability index of the system of the maximum power angle difference of the generator by using the following formula <6 >:

_max＝max|_i-_j| <6>；

wherein,_iand_jthe power angles of any two generators in the transient process after the fault is removed;

5) the economic index is as follows:

the economic indexes of the current-limiting scheme comprise direct investment cost and indirect investment cost of the adopted measures and system operation network loss cost; the direct investment cost comprises the investment increased by adopting a high-impedance transformer and a series reactor device, and the indirect investment cost comprises the cost related to engineering construction;

by the formula<7>Calculating an economic indicator E_loss：

E_loss＝M_invd+M_invind+M_Ploss <7>；

Wherein M is_invdRepresents a direct investment cost; m_invindRepresents an indirect investment cost; m_PlossRepresenting increased network loss costs.

3. The short-circuit current suppression scheme evaluation method according to claim 1, wherein the step (2) comprises the steps of:

setting an evaluation matrix of evaluation indexes of a short-circuit current suppression scheme;

standardizing the original evaluation indexes;

defining the entropy of the evaluation index;

and fourthly, defining an evaluation index entropy weight.

4. The short-circuit current suppression scheme evaluation method according to claim 3, characterized in that said step (r) includes: let the evaluation index vector of j short-circuit current suppression schemes be X_j＝[x_1j,x_2j,x_3j,x_4j,x_5j]^TWherein x is_1jThree-phase short-circuit current, x, of bus of 220kV power grid_2jIs the main variable load rate, x_3jFor bus voltage out-of-limit and line overload indicators, x_4jIs the maximum power angle difference, x, between two generators_5jIs an economic index;

if there are n short-circuit current suppression schemes, the evaluation matrix is represented as X ═ X₁,X₂,…,X_n](ii) a The weight of the short-circuit current suppression scheme evaluation index is represented by ω, and the weight vector is ω ═ ω₁,ω₂,...,ω_i]^Ti is 5; wherein i represents an evaluation index number;

the expression X ═ X (X) for establishing the evaluation matrix_ij)_m×nWhere m is the number of evaluation indexes and n is the number of objects to be evaluated.

5. The short-circuit current suppression scheme evaluation method according to claim 3, wherein the step (ii) includes: if the m evaluation indexes have negative indexes, namely indexes with smaller index values and better conditions are represented, firstly carrying out index homologization processing, converting the indexes into positive indexes and carrying out unified processing, wherein the positive indexes have better conditions reflected when the index values are larger;

carrying out standardization processing on the original evaluation matrix by adopting an equation (9) and an equation (10), converting a negative index into a positive index and normalizing all indexes; the raw evaluation matrix is normalized to obtain:

R＝(r_ij)_m×n <8>；

in the formula, r_ij-the standard value, r, of the jth evaluation object on the ith evaluation index_ij∈[0,1]；

For the forward direction index, the normalization process is as follows:

$r_{\mathrm{ij}}=\frac{x_{\mathrm{ij}}-\min \left\{x_{\mathrm{ij}}\right\}}{\max \left\{x_{\mathrm{ij}}\right\}-\min \left\{x_{\mathrm{ij}}\right\}}---<9>;$

for the negative indicators, the normalization process is:

$r_{\mathrm{ij}}=\frac{\max \left\{x_{\mathrm{ij}}\right\}-x_{\mathrm{ij}}}{\max \left\{x_{\mathrm{ij}}\right\}-\min \left\{x_{\mathrm{ij}}\right\}}---<10>;$

wherein r is_ijElements of the standard evaluation matrix.

6. The method for evaluating a short-circuit current suppression scheme according to claim 3, wherein the step (c) includes: in the evaluation problem with m evaluation indexes and n evaluation objects, the entropy H of the ith index_iIs defined as:

<math> <mrow> <msub> <mi>H</mi> <mi>i</mi> </msub> <mo>=</mo> <mo>-</mo> <mi>k</mi> <munderover> <mi>&Sigma;</mi> <mrow> <mi>j</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>n</mi> </munderover> <msub> <mi>f</mi> <mi>ij</mi> </msub> <mi>ln</mi> <msub> <mi>f</mi> <mi>ij</mi> </msub> <mo>,</mo> <mi>i</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>m</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>11</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula:k is 1/lnn, when f_ijWhen equal to 0, let f_ijlnf_ij＝0；f_ijRepresents a normalized value; k denotes an adjustment coefficient.

7. The evaluation method for short-circuit current suppression scheme according to claim 3, wherein in the step (r), the entropy weight w of the ith index_iIs defined as:

<math> <mrow> <msub> <mi>w</mi> <mi>i</mi> </msub> <mo>=</mo> <mfrac> <mrow> <mn>1</mn> <mo>-</mo> <msub> <mi>H</mi> <mi>i</mi> </msub> </mrow> <mrow> <mi>m</mi> <mo>-</mo> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>H</mi> <mi>i</mi> </msub> </mrow> </mfrac> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>12</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

in the formula, w is more than or equal to 0_i≤1， <math> <mrow> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msub> <mi>w</mi> <mi>i</mi> </msub> <mo>=</mo> <mn>1</mn> <mo>.</mo> </mrow> </math>

8. The short-circuit current suppression scheme evaluation method according to claim 1, wherein the step (3) includes the steps of:

A. calculating the distance from the sample point to the reference point;

B. the relative proximity is calculated.

9. As claimed in claimThe evaluation method of the short-circuit current suppression scheme is characterized in that in the step A, the weight determined by an entropy weight method is used according to the formula<13>Determining a weighted data matrix Z ═ Z_ij]_m×n：

Z＝R·ω <13>；

Wherein: r represents the normalized evaluation matrix; omega represents an entropy weight;

the evaluation indexes are normalized, the maximum value of each index in all samples is used for forming an ideal sample, the minimum value of each index is used for forming a negative ideal sample, and Z is used respectively⁺And Z^-Represents;

defining the distance from the sample point to the optimal point as D +, which is calculated as shown in equation <14 >:

<math> <mrow> <msubsup> <mi>D</mi> <mi>j</mi> <mo>+</mo> </msubsup> <mo>=</mo> <msqrt> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>ij</mi> </msub> <mo>-</mo> <msubsup> <mi>z</mi> <mi>i</mi> <mo>+</mo> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </msqrt> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>n</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>14</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

defining the distance from the sample point to the worst point as D-, which is calculated as shown in equation <15 >:

<math> <mrow> <msubsup> <mi>D</mi> <mi>j</mi> <mo>-</mo> </msubsup> <mo>=</mo> <msqrt> <munderover> <mi>&Sigma;</mi> <mrow> <mi>i</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>m</mi> </munderover> <msup> <mrow> <mo>(</mo> <msub> <mi>z</mi> <mi>ij</mi> </msub> <mo>-</mo> <msubsup> <mi>z</mi> <mi>i</mi> <mo>-</mo> </msubsup> <mo>)</mo> </mrow> <mn>2</mn> </msup> </msqrt> <mo>,</mo> <mi>j</mi> <mo>=</mo> <mn>1,2</mn> <mo>,</mo> <mo>.</mo> <mo>.</mo> <mo>.</mo> <mo>,</mo> <mi>n</mi> <mo>-</mo> <mo>-</mo> <mo>-</mo> <mo>&lt;</mo> <mn>15</mn> <mo>></mo> <mo>;</mo> </mrow> </math>

wherein: z is a radical of_ijRepresenting elements in a weighted data matrix Z;an ideal sample representing the ith index;representing a negative ideal sample of the ith index.

10. The short-circuit current suppression scheme evaluation method according to claim 8, wherein in the step B, the relative proximity is calculated by an equation <16 >:

$C_j=\frac{D_j^{-}}{D_j^{-}+D_j^{+}}---<16>;$

according to relative proximity C_jThe size of (2), sorting each evaluation object; c_jThe larger the distance between the evaluation object and the ideal sample, the better the evaluation result of the evaluation object.