CN110689240A - Fuzzy comprehensive evaluation method for economic operation of power distribution network - Google Patents
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Abstract
The invention provides a fuzzy comprehensive evaluation method for economic operation of a power distribution network, which comprises the following steps: s1, establishing a power distribution network economic operation evaluation index system; s2, establishing a comment set, and generating a standardized evaluation matrix of the economic operation evaluation index of the power distribution network according to the comment set; s3, carrying out weight calculation on each power distribution network economic operation evaluation index based on entropy correction AHP weighting; and S4, establishing a fuzzy calculation model of economic operation of the power distribution network, and performing fuzzy processing calculation on the standardized evaluation matrix. The fuzzy comprehensive evaluation method for the economic operation of the power distribution network provided by the invention avoids the ambiguity and randomness of the grading boundary information in the current comprehensive evaluation for the economic operation of the power distribution network, reasonably processes the uncertainty of expert judgment, and simultaneously avoids the problem of the dispersion of comprehensive acquisition parameters.
Description
Technical Field
The invention belongs to the technical field of power distribution network economic operation evaluation, and particularly relates to a fuzzy comprehensive evaluation method for power distribution network economic operation.
Background
With the reform of the power system, people pay more and more attention to economic benefits, and the loss of a power distribution network accounts for more than half of the total loss of the power grid. The economic operation of the power distribution network is an energy-saving technology with strong practicability, and various losses of a power supply line and a distribution transformer are reduced to the maximum extent through various technical measures on the basis of ensuring the safe operation and the power supply quality of the power distribution network, so that the scale benefit of the network is exerted. The economic operation level of the power distribution network is improved, and the method has important significance for building a conservation-oriented society and improving economic benefits.
At present, no technical scheme for effectively evaluating the economical efficiency of the operation of the power distribution network exists, weak links in the operation of the power distribution network cannot be found, and the economical operation and loss reduction of the power distribution network lack technical support. The existing economic evaluation scheme for the operation of the power distribution network has the problems of ambiguity and randomness, uncertainty in judgment of experts and comprehensive inter-regional number divergence.
Therefore, in order to overcome the above-mentioned shortcomings in the prior art, it is necessary to provide a fuzzy comprehensive evaluation method for economic operation of a power distribution network.
Disclosure of Invention
The invention provides a fuzzy comprehensive evaluation method for economic operation of a power distribution network, aiming at the defects that the existing economic evaluation scheme for operation of the power distribution network in the prior art has ambiguity and randomness, and experts judge that uncertainty exists and the comprehensive gains are scattered, and aims to solve the technical problems.
The invention provides a fuzzy comprehensive evaluation method for economic operation of a power distribution network, which comprises the following steps:
s1, establishing a power distribution network economic operation evaluation index system;
s2, establishing a comment set, and generating a standardized evaluation matrix of the economic operation evaluation index of the power distribution network according to the comment set;
s3, carrying out weight calculation on each power distribution network economic operation evaluation index based on entropy correction AHP weighting;
and S4, establishing a fuzzy calculation model of economic operation of the power distribution network, and performing fuzzy processing calculation on the standardized evaluation matrix.
Further, the step S1 specifically includes the following steps:
s11, establishing a power distribution network economic operation evaluation index system according to the power distribution network economic operation requirement;
s12, generating a hierarchical framework of the economic operation evaluation index system of the power distribution network, wherein the hierarchical framework comprises a target layer, a criterion layer and a factor layer;
s13, generating elements of a quasi-measurement layer under a target layer of the power distribution network economic operation evaluation index system;
and S14, generating evaluation index elements of the factor layer under each quasi-measurement layer of the power distribution network economic operation evaluation index system. Determining factors influencing the economic operation of the power distribution network, and constructing a power distribution network economic operation evaluation index system according to a classification and layering principle.
Further, the elements of the quasi-measurement layer in step S13 include voltage quality, grid loss, power factor, load, distribution network equipment, and grid layout. The criteria layer includes, but is not limited to, the categories described above.
Further, the factor layer elements of the voltage quality comprise a voltage deviation qualified rate, a bus voltage qualified rate and a voltage deviation rate qualified rate; the elements of the power grid damage factor layer comprise a line theoretical loss rate, a line statistical loss rate and a distribution transformer theoretical loss qualified rate; the factor layer elements of the power factor comprise a line power factor and a distribution transformation power factor qualification rate; the factor layer elements of the load comprise an optimal load area of the line, a load rate of the line, a qualification rate of a distribution transformation load rate and a three-phase unbalance degree of the load; the factor layer elements of the power distribution network equipment comprise a line guide sectional area qualification rate, a line insulation rate, a distribution transformer load rate qualification rate, a high-energy-consumption transformer number ratio and a high-energy-consumption transformer capacity ratio; the factor layer elements of the power grid layout comprise the line power supply radius, the load center ratio of distribution transformer, capacitor switching, the operation mode, the line capacity-load ratio and the matching degree of the lead transformer. Factors for each criteria layer include, but are not limited to, those described above.
Further, the step S2 specifically includes the following steps:
s21, dividing the economic operation state of the power distribution network into at least five grades according to a fuzzy mathematical theory, and generating a comment set;
s22, evaluating each index in the power distribution network economic operation evaluation index system by adopting a comment set to generate an evaluation matrix;
and S23, carrying out standardization processing on the evaluation matrix to generate a standardized evaluation matrix. Aiming at indexes in an index evaluation system, obtaining an evaluation matrix of the power distribution network by a comment set;
further, a five-level panel of comments, including excellent, good, qualified, attentive, and severe, is generated in step S21. According to the fuzzy mathematical theory, the five-level system can accurately describe the economic operation of the power distribution network.
Further, the step S3 specifically includes the following steps:
s31, calculating an entropy value of each evaluation index under a power distribution network economic operation evaluation index system;
s32, respectively sequencing the importance of each evaluation index and each quasi-measurement layer according to the calculated entropy value;
s33, generating a judgment matrix according with random consistency ratio according to the importance sequence;
and S34, calculating the weight of each evaluation index according to the judgment matrix. And respectively sorting the importance of the index layer and the criterion layer according to the calculated entropy value.
Further, the step S32 specifically includes the following steps:
s321, ranking the importance of each evaluation index according to the entropy value of the calculated evaluation index;
s322, calculating the average number of evaluation index entropy values in each quasi-measuring layer to serve as the entropy values of the quasi-measuring layers;
and S323, carrying out importance sequencing on each quasi-measuring layer according to the entropy value of the quasi-measuring layer. Firstly, ranking the importance of evaluation indexes; secondly, ranking the importance of the criterion layers, taking the average of index entropy values in each criterion layer as the entropy value of the criterion layer, and ranking the importance degree of each criterion layer.
Further, the step S33 specifically includes the following steps:
s331, establishing a judgment matrix between every two evaluation indexes according to the importance degree of the evaluation indexes in each quasi-measurement layer;
s332, calculating a random consistency ratio of the judgment matrix, and judging whether the random consistency ratio is smaller than a set value;
if yes, go to step S34;
if not, adjusting and correcting the judgment matrix, and returning to the step S332. Firstly, calculating the weight of an index layer to a criterion layer, and respectively sequencing evaluation indexes under each criterion layer according to the calculated entropy value to determine the importance degree of the evaluation indexes in each criterion layer so as to construct a judgment matrix between every two indexes; and the judgment matrix is adjusted and corrected to ensure that the judgment matrix passes consistency check.
Further, the step S4 specifically includes the following steps:
s41, generating a membership degree set corresponding to the comment set according to a modulus membership degree principle;
s42, generating a second evaluation matrix according to all evaluation indexes in the membership set;
s43, generating a weighted average type fuzzy comprehensive evaluation model according to the weight of each evaluation index;
and S44, judging the second evaluation matrix by adopting a weighted average fuzzy comprehensive judgment model to obtain a fuzzy comprehensive judgment result. Converting qualitative evaluation into quantitative evaluation according to membership theory of fuzzy mathematics, namely making an overall evaluation on objects or objects restricted by various factors by the fuzzy mathematics; and aiming at the characteristics of the operation of the power distribution network, evaluating the operation economy of the power distribution network by applying a fuzzy comprehensive evaluation method.
Further, in step S44, the maximum value in the fuzzy comprehensive evaluation result is obtained as the final evaluation result according to the maximum membership rule.
The beneficial effect of the invention is that,
the fuzzy comprehensive evaluation method for the economic operation of the power distribution network provided by the invention avoids the ambiguity and randomness of the grading boundary information in the current comprehensive evaluation for the economic operation of the power distribution network, reasonably processes the uncertainty of expert judgment, and simultaneously avoids the problem of the dispersion of comprehensive acquisition parameters.
In addition, the invention has reliable design principle, simple structure and very wide application prospect.
Therefore, compared with the prior art, the invention has prominent substantive features and remarkable progress, and the beneficial effects of the implementation are also obvious.
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In order to more clearly illustrate the embodiments or technical solutions in the prior art of the present invention, the drawings used in the description of the embodiments or prior art will be briefly described below, and it is obvious for those skilled in the art that other drawings can be obtained based on these drawings without creative efforts.
FIG. 1 is a first schematic flow chart of the method of the present invention;
FIG. 2 is a second schematic flow chart of the method of the present invention;
FIG. 3 is a third schematic flow chart of the method of the present invention;
FIG. 4 is a schematic diagram of an evaluation index system for the operation of the power distribution network in example 4;
FIG. 5 is a schematic diagram of the distribution function form of the triangle and half trapezoid combination used in generating the membership set corresponding to the comment set in example 4;
fig. 6 is a schematic diagram of state data of each index in the economic evaluation index system of the power distribution network in embodiment 4;
FIG. 7 is a weight diagram of each index of the power distribution network according to the method for correcting the AHP based on entropy sorting in embodiment 4;
fig. 8 is a schematic diagram of a fuzzy comprehensive evaluation result of economic operation of the power distribution network in embodiment 4 based on entropy correction AHP weighting.
Detailed Description
In order to make those skilled in the art better understand the technical solution of the present invention, the technical solution in the embodiment of the present invention will be clearly and completely described below with reference to the drawings in the embodiment of the present invention, and it is obvious that the described embodiment is only a part of the embodiment of the present invention, and not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1:
as shown in fig. 1, the invention provides a fuzzy comprehensive evaluation method for economic operation of a power distribution network, which comprises the following steps:
s1, establishing a power distribution network economic operation evaluation index system;
s2, establishing a comment set, and generating a standardized evaluation matrix of the economic operation evaluation index of the power distribution network according to the comment set;
s3, carrying out weight calculation on each power distribution network economic operation evaluation index based on entropy correction AHP weighting;
and S4, establishing a fuzzy calculation model of economic operation of the power distribution network, and performing fuzzy processing calculation on the standardized evaluation matrix.
Example 2:
as shown in fig. 2, the invention provides a fuzzy comprehensive evaluation method for economic operation of a power distribution network, which comprises the following steps:
s1, establishing a power distribution network economic operation evaluation index system; the method comprises the following specific steps:
s11, establishing a power distribution network economic operation evaluation index system according to the power distribution network economic operation requirement;
s12, generating a hierarchical framework of the economic operation evaluation index system of the power distribution network, wherein the hierarchical framework comprises a target layer, a criterion layer and a factor layer;
s13, generating elements of a quasi-measurement layer under a target layer of the power distribution network economic operation evaluation index system;
s14, generating evaluation index elements of a factor layer under each quasi-measurement layer of the power distribution network economic operation evaluation index system;
s2, establishing a comment set, and generating a standardized evaluation matrix of the economic operation evaluation index of the power distribution network according to the comment set; the method comprises the following specific steps:
s21, dividing the economic operation state of the power distribution network into at least five grades according to a fuzzy mathematical theory, and generating a comment set;
s22, evaluating each index in the power distribution network economic operation evaluation index system by adopting a comment set to generate an evaluation matrix;
s23, standardizing the evaluation matrix to generate a standardized evaluation matrix;
s3, carrying out weight calculation on each power distribution network economic operation evaluation index based on entropy correction AHP weighting; the method comprises the following specific steps:
s31, calculating an entropy value of each evaluation index under a power distribution network economic operation evaluation index system;
s32, respectively sequencing the importance of each evaluation index and each quasi-measurement layer according to the calculated entropy value;
s33, generating a judgment matrix according with random consistency ratio according to the importance sequence;
s34, calculating the weight of each evaluation index according to the judgment matrix;
s4, establishing a fuzzy calculation model of economic operation of the power distribution network, and performing fuzzy processing calculation on the standardized evaluation matrix; the method comprises the following specific steps:
s41, generating a membership degree set corresponding to the comment set according to a modulus membership degree principle;
s42, generating a second evaluation matrix according to all evaluation indexes in the membership set;
s43, generating a weighted average type fuzzy comprehensive evaluation model according to the weight of each evaluation index;
and S44, judging the second evaluation matrix by adopting a weighted average fuzzy comprehensive judgment model to obtain a fuzzy comprehensive judgment result.
Example 3:
unlike embodiment 2, as shown in fig. 3,
the step S32 includes the following steps:
s321, ranking the importance of each evaluation index according to the entropy value of the calculated evaluation index;
s322, calculating the average number of evaluation index entropy values in each quasi-measuring layer to serve as the entropy values of the quasi-measuring layers;
s323, carrying out importance ranking on each quasi-measuring layer according to the entropy value of the quasi-measuring layer;
the step S33 includes the following steps:
s331, establishing a judgment matrix between every two evaluation indexes according to the importance degree of the evaluation indexes in each quasi-measurement layer;
s332, calculating a random consistency ratio of the judgment matrix, and judging whether the random consistency ratio is smaller than a set value;
if yes, go to step S34;
if not, adjusting and correcting the judgment matrix, and returning to the step S332.
Example 4:
the invention provides a fuzzy comprehensive evaluation method for economic operation of a power distribution network, which comprises the following steps:
s1, establishing a power distribution network economic operation evaluation index system; the method comprises the following specific steps:
s11, establishing a power distribution network economic operation evaluation index system according to the power distribution network economic operation requirement;
s12, generating a hierarchical framework of the economic operation evaluation index system of the power distribution network, wherein the hierarchical framework comprises a target layer, a criterion layer and a factor layer; evaluating the economic progress of the power distribution network at a target layer of the economic operation evaluation of the power distribution network;
s13, generating elements of a quasi-measurement layer under a target layer of the power distribution network economic operation evaluation index system; according to different attributes of the influencing factors, 6 criteria layer element indexes are set: power grid quality, power grid loss, power factor, load, distribution network equipment and power grid layout;
s14, generating evaluation index elements of a factor layer under each quasi-measurement layer of the power distribution network economic operation evaluation index system; each criterion layer comprises a plurality of factor layer element indexes, the index number is 23, the specific content of each factor layer index is shown in figure 4, and the index system can comprehensively realize the coverage of factors influencing the economic operation of the power distribution network;
s2, establishing a comment set, and generating a standardized evaluation matrix of the economic operation evaluation index of the power distribution network according to the comment set; the method comprises the following specific steps:
s21, dividing the economic operation state of the power distribution network into five grades of 'excellent', 'good', 'qualified', 'noticed' and 'serious' according to a fuzzy mathematical theory, and generating a comment set;
l ═ excellent, good, qualified, attentive, severe }
＝{l1,l2,l3,l4,l5}
S22, evaluating each index in the power distribution network economic operation evaluation index system by adopting a comment set to generate an evaluation matrix;
s23, standardizing the evaluation matrix to generate a standardized evaluation matrix;
setting forward indexes in a grading way: pikThe k index score, V, for the i-th evaluation objectikThe forward index scoring formula is that the forward index scoring formula is the original data of the kth index of the ith evaluation object, and n is the number of the evaluated objects:
the economic meaning in the formula is the relative distance between the deviation of the kth index value and the minimum value of the ith evaluation object relative to the deviation of the maximum and minimum values, and the higher the score is, the better the index development condition is;
the meaning of each symbol of the negative index scoring is consistent with that of the positive index scoring formula, and the negative index scoring formula is as follows:
the economic meaning is the same as the positive index scoring formula;
after normalization, the normalized evaluation matrix is obtained as:
s3, carrying out weight calculation on each power distribution network economic operation evaluation index based on entropy correction AHP weighting; the method comprises the following specific steps:
s31, calculating an entropy value of each evaluation index under a power distribution network economic operation evaluation index system;
calculating the entropy of each index to reflect the variation degree of the evaluated index, and reflecting the information quantity according to the variation degree of the data, wherein the more scattered the distribution of the index data is, the larger the information quantity provided by the index is, the larger the weight occupied in the comprehensive evaluation is; on the contrary, the more concentrated the distribution of the index data is, the smaller the information amount provided by the index is, the smaller the occupied weight is;
let VikRaw data (i ═ 1,2, …, n; k ═ 1,2, …, m) of the kth evaluation index of the ith evaluation object,
for the entropy value of the k index of the j criterion layer (j ═ 1,2, …, q), the entropy value is calculated
The calculation formula of (2) is as follows:
s32, respectively sequencing the importance of each evaluation index and each quasi-measurement layer according to the calculated entropy value; the method comprises the following specific steps:
s321. according to calculationEntropy of evaluation index
Ranking the importance of each evaluation index;
s322, calculating the average number of evaluation index entropy values in each quasi-measuring layer to serve as the entropy values of the quasi-measuring layers;
entropy e of the jth criterion layer(j)The calculation formula is as follows:
s323, carrying out importance ranking on each quasi-measuring layer according to the entropy value of the quasi-measuring layer; calculated e(j)The values can sort the importance degrees of all the criterion layers, if the entropy values of some two criterion layers are equal, the importance degrees of the two criterion layers are considered to be the same, and the importance scale is 1;
s33, generating a judgment matrix according with random consistency ratio according to the importance sequence; the method comprises the following specific steps:
s331, establishing a judgment matrix between every two evaluation indexes according to the importance degree of the evaluation indexes in each quasi-measurement layer; according to
Respectively sequencing evaluation indexes under each criterion layer by the entropy value calculated by the calculation formula to determine the importance degree of the evaluation indexes in each criterion layer, and further constructing a judgment matrix between every two indexes;
s332, calculating a random consistency ratio of the judgment matrix, and judging whether the random consistency ratio is smaller than a set value;
if yes, go to step S34;
if not, adjusting and correcting the judgment matrix, and returning to the step S332;
after the judgment matrix among the indexes is determined, the random consistency ratio CR is utilized to carry out consistency check, and the calculation formula is as follows:
wherein, λ is the maximum eigenvalue of the judgment matrix, n is the number of the evaluated objects, and RI is the average random consistency index. If the random consistency ratio CR is less than 0.1, the judgment matrix is considered to pass the consistency test; otherwise, the judgment matrix needs to be adjusted and corrected until the consistency test is passed;
s34, calculating the weight of each evaluation index according to the judgment matrix; let a be the importance scale of the kth index relative to the tth index in the decision matrixkt(k is 1,2, …, n; t is 1,2, …, n), and the weights of the evaluation indexes can be calculated according to the judgment matrix, and the steps are as follows:
and carrying out normalization processing on each column of the judgment matrix, wherein the normalization formula is as follows:
and adding the normalized matrixes in rows to obtain:
and carrying out column normalization processing on the obtained vector, wherein the calculation formula is as follows:
u＝(u1,u2,…,un)T
then u is (u)1,u2,…,un)TI.e., an index weight vector, where ukRepresenting the weight occupied by the k index in the criterion layer;
let the weight of the jth criterion layer to the target layer be u(j)，wkFor the weight of the k index in the j criterion layer to the total target layer, u(j)The weight of the jth criterion layer to the total target layer is calculated as follows:
wk＝uk×u(j)；
s4, establishing a fuzzy calculation model of economic operation of the power distribution network, and performing fuzzy processing calculation on the standardized evaluation matrix; the method comprises the following specific steps:
s41, generating a membership degree set corresponding to the comment set according to a modulus membership degree principle; the membership function represents the degree or grade of the fuzzy set L, namely a fuzzy characteristic function; in the power distribution network economic fuzzy comprehensive evaluation model, comment factors have both qualitative factors and quantitative factors, and a distribution function form of combination of a triangular form and a semi-trapezoidal form is selected according to the data characteristics of a factor set, as shown in FIG. 5;
the specific determination method of the membership function comprises the following steps: according to related design data, experimental results and monitoring data, determining distribution functions of triangles and semi-trapezoids shown in figure 5, giving fuzzy boundary intervals of five state grades, and finally establishing membership functions of the state grades. For example, for the operation mode evaluation index, the corresponding state membership functions are respectively as follows:
in the formula I1～l5And respectively corresponding to the membership functions of each state when the operation mode of the power distribution network is x. The membership functions of other evaluation indexes can be obtained in the same way;
by evaluation index CijEvaluating the economic running state of the power distribution network and evaluating the concentrated state lij(i ═ 1,2,3,4,5) with degree of membership vij(j ═ 1,2,3,4,5), then the set of membership degrees can be used:
Vi＝{vi1,vi2,vi3,vi4,vi5}
indicates the index CijThe result of the evaluation;
s42, generating a second evaluation matrix according to all evaluation indexes in the membership set;
all the evaluation indexes of the sub-item layer form an evaluation matrix thereof, wherein CijThe j-th judgment index in the ith item is obtained. Such as by the inherent factor B in the project layer1For example, the evaluation matrix is
S43, generating a weighted average type fuzzy comprehensive evaluation model according to the weight of each evaluation index;
s44, judging the second evaluation matrix by adopting a weighted average fuzzy comprehensive judgment model to obtain a fuzzy comprehensive judgment result;
in order to ensure the objectivity and authenticity of the fuzzy comprehensive evaluation result, the influence of main evaluation indexes on the pollution flashover state of the insulator is considered, and all information of a single evaluation index is reserved, so that the method selects a weighted average type fuzzy comprehensive evaluation model, and uses M (+,) to obtain the result
The final fuzzy comprehensive evaluation result is
C＝(c1,c2,…,cn)；
The operation is a boundary sum operation, not only considers the influence of main factors, but also considers the influence of non-main factors, and is suitable for judging the comprehensive indexes of the system. The vector C is the comprehensive judgment result, and is the maximum C according to the maximum membership rulejIs corresponding toiThe evaluation result of (1).
The invention takes an area 10kV power distribution network actually operated by a certain power company as an example, and comprises 104 10kV operation lines and 4697 distribution transformers (1546 public transformers and 3151 private transformers). Carrying out load flow calculation, asset statistics and other detailed calculation analysis according to representative day actual operation data provided by an SCADA (data acquisition and monitoring control system) and a power grid theoretical line loss calculation system to obtain each index data of the power distribution network, as shown in FIG. 6; the method for correcting the AHP based on the entropy sequencing is characterized in that the obtained index weight is shown in FIG. 7; the evaluation result of the power distribution network obtained according to the original data of the power distribution network is given in fig. 8;
it can be known from fig. 8 that the final evaluation result of the distribution network is 80.65, the score is generally high in the overall aspect of the factor layer indexes, but some indexes are low, the index score of the power grid loss is low, the operation state is poor, weak links in the power grid can be clearly found according to the factor layer index score, targeted technical transformation can be performed, the weak links also have certain influence on the overall economy, the index can be adjusted on the basis of adjusting the line loss and reactive power optimization, and therefore the economy of the distribution network operation is improved.
The power staff can take some measures on the index with the lower evaluation score, such as adjusting or even modifying the power grid, so that the economy of the overall operation of the power grid is improved. Through evaluation, the economy of the operation of the power grid can be known, and workers can judge relevant factors influencing the economy of the operation of the distribution network according to corresponding results, so that the formulation and the direction of the transformation scheme are clearly answered.
Although the present invention has been described in detail by referring to the drawings in connection with the preferred embodiments, the present invention is not limited thereto. Various equivalent modifications or substitutions can be made on the embodiments of the present invention by those skilled in the art without departing from the spirit and scope of the present invention, and these modifications or substitutions are within the scope of the present invention/any person skilled in the art can easily conceive of the changes or substitutions within the technical scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope of the claims.
Claims (10)
1. A power distribution network economic operation fuzzy comprehensive evaluation method is characterized by comprising the following steps:
s1, establishing a power distribution network economic operation evaluation index system;
s2, establishing a comment set, and generating a standardized evaluation matrix of the economic operation evaluation index of the power distribution network according to the comment set;
s3, carrying out weight calculation on each power distribution network economic operation evaluation index based on entropy correction AHP weighting;
and S4, establishing a fuzzy calculation model of economic operation of the power distribution network, and performing fuzzy processing calculation on the standardized evaluation matrix.
2. The fuzzy comprehensive evaluation method for the economic operation of the power distribution network according to claim 1, wherein the step S1 comprises the following steps:
s11, establishing a power distribution network economic operation evaluation index system according to the power distribution network economic operation requirement;
s12, generating a hierarchical framework of the economic operation evaluation index system of the power distribution network, wherein the hierarchical framework comprises a target layer, a criterion layer and a factor layer;
s13, generating elements of a quasi-measurement layer under a target layer of the power distribution network economic operation evaluation index system;
and S14, generating evaluation index elements of the factor layer under each quasi-measurement layer of the power distribution network economic operation evaluation index system.
3. The fuzzy evaluation method for economic operation of the power distribution network according to claim 2, wherein the elements of the quasi-measurement layer in the step S13 include voltage quality, power grid loss, power factor, load, power distribution network equipment and power grid layout.
4. The fuzzy comprehensive evaluation method for the economic operation of the power distribution network according to claim 2, wherein the step S2 comprises the following steps:
s21, dividing the economic operation state of the power distribution network into at least five grades according to a fuzzy mathematical theory, and generating a comment set;
s22, evaluating each index in the power distribution network economic operation evaluation index system by adopting a comment set to generate an evaluation matrix;
and S23, carrying out standardization processing on the evaluation matrix to generate a standardized evaluation matrix.
5. The fuzzy evaluation method for economic operation of power distribution network according to claim 4, wherein in step S21, a five-level comment set is generated, which includes excellent, good, qualified, attentive and serious.
6. The fuzzy comprehensive evaluation method for the economic operation of the power distribution network according to claim 4, wherein the step S3 comprises the following steps:
s31, calculating an entropy value of each evaluation index under a power distribution network economic operation evaluation index system;
s32, respectively sequencing the importance of each evaluation index and each quasi-measurement layer according to the calculated entropy value;
s33, generating a judgment matrix according with random consistency ratio according to the importance sequence;
and S34, calculating the weight of each evaluation index according to the judgment matrix.
7. The fuzzy comprehensive evaluation method for the economic operation of the power distribution network according to claim 6, wherein the step S32 comprises the following steps:
s321, ranking the importance of each evaluation index according to the entropy value of the calculated evaluation index;
s322, calculating the average number of evaluation index entropy values in each quasi-measuring layer to serve as the entropy values of the quasi-measuring layers;
and S323, carrying out importance sequencing on each quasi-measuring layer according to the entropy value of the quasi-measuring layer.
8. The fuzzy comprehensive evaluation method for economic operation of the power distribution network according to claim 1,
the step S33 includes the following steps:
s331, establishing a judgment matrix between every two evaluation indexes according to the importance degree of the evaluation indexes in each quasi-measurement layer;
s332, calculating a random consistency ratio of the judgment matrix, and judging whether the random consistency ratio is smaller than a set value;
if yes, go to step S34;
if not, adjusting and correcting the judgment matrix, and returning to the step S332.
9. The fuzzy comprehensive evaluation method for the economic operation of the power distribution network according to claim 6, wherein the step S4 comprises the following steps:
s41, generating a membership degree set corresponding to the comment set according to a modulus membership degree principle;
s42, generating a second evaluation matrix according to all evaluation indexes in the membership set;
s43, generating a weighted average type fuzzy comprehensive evaluation model according to the weight of each evaluation index;
and S44, judging the second evaluation matrix by adopting a weighted average fuzzy comprehensive judgment model to obtain a fuzzy comprehensive judgment result.
10. The fuzzy comprehensive evaluation method for economic operation of the power distribution network according to claim 9, wherein in step S44, the maximum value in the fuzzy comprehensive evaluation results is obtained as the final evaluation result according to the maximum membership rule.
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