CN109784778A - A kind of Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights - Google Patents
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Abstract
The invention belongs to electric network synthetic assessment technique field more particularly to a kind of Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights, include the following steps: that S1. establishes the Electric Power Network Planning indicator evaluation system for adapting to electricity market reform；S2. each index weights in index system are determined based on combination weights method；S3. each achievement data for handling programme to be evaluated is collected, Electric Power Network Planning model of fuzzy synthetic evaluation is established.This method considers the entitled subjectivity of expert, handles with combination weights method multiple expert judgments results, improves the science and practicability of evaluation criterion weight, and carry out comprehensive evaluation to power network planning scheme.
Description
Technical field
The invention belongs to electric network synthetics to evaluate field, obscure more particularly, to a kind of Electric Power Network Planning based on combination weights comprehensive
Close evaluation method.
Background technique
The change that grid requirements after electricity market reform are not accounted in existing Electric Power Network Planning index, primarily directed to
In terms of certain, such as the evaluation of reliability, low carbon development to power grid, and weight is determined and mainly uses expert's enabling legislation,
Its result subjectivity is too strong, and expert opinion disunity may influence the result of overall merit.
Summary of the invention
In view of the above-mentioned problems, the present invention proposes a kind of Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights,
Weight uses combination weights method in determining, carries out adapting to electricity market reform overall merit to Electric power network planning method.This method
The change under electricity market reform to grid requirements is considered, the metrics evaluation body for adapting to electricity market reform is established
System, and weight determine in, it is contemplated that the entitled subjectivity of expert, with combination weights method to multiple expert judgments results into
Row processing, improves the science and practicability of evaluation criterion weight.This method specifically:
A kind of Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights, which comprises the steps of:
S1. the Electric Power Network Planning indicator evaluation system for adapting to electricity market reform is established；
S2. each index weights in index system are determined based on combination weights method；
S3. each achievement data for handling programme to be evaluated is collected, Electric Power Network Planning model of fuzzy synthetic evaluation is established.
In a kind of above-mentioned Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights, the step S1 is specifically wrapped
It includes:
S1-1. according to electricity market reform the characteristics of, the index of screening reliability, economy and Environmental three aspect；
S1-2. the definition and calculation method of clear index, establishes indicator evaluation system.
In a kind of above-mentioned Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights, the step S2 is specifically wrapped
It includes:
S2-1. multiple expert judgments are acquired as a result, being specifically:
The interior multidigit authoritative expert that chooses a trade carries out weight judgement, and every expert writes judgment matrix by column and directly assigns power
Mode determine index weights.For the upper layer index of the next layer of index containing there are three or more, write using Satty rule column
Judgment matrix, for containing there are two and lower layer's index below upper layer index, selection directly entitled method column write assignment to
Amount.
In formula: U1, U2, U3Reliability in assessment indicator system, economy and Environmental three first class index are referred respectively to,
aijFor first class index UiAnd UjFor the judgement numerical value of the significance level of entire evaluation goal.
In formula: U21And U22Refer respectively to the input-occupancy-output analysis and output index under economic index, ciFor economic index institute
Including two-level index U2iThe ratio accounted in economic index, and meet c1+c2=1.
S2-2. the weight judging result for merging and obtaining each expert is calculated, the weight of each judgment matrix is specifically calculated
Vector, and consistency judgement is carried out, according to the weight vectors and adele of each expert of the layer-by-layer merger of analytic hierarchy process (AHP), synthesis
Obtain the weight judging result of each expert.According to n factor in the obtained rule layer of judgment matrix A for the power of destination layer
Weight coefficient is α=(α1,α2,...,αi,...,αn)T, l under i-th of rule layer factoriWeight system of a index for this criterion
Number isThen the index under the rule layer factor is for the weight coefficient of destination layerThen all index factors for destination layer total weight coefficient, i.e.,
The total weight of single human expert judges that data are
γ=(γ1,γ2,...,γn)T=(α1β1,α2β2,...,αnβn)T (3)
S2-3. according to improved Gray Correlation synthetic population comprehensive weight, index weights matrix is obtained, is specifically included
1) there is n lowest level index in assessment indicator system, there is m expert to judge these index weights, then
Expert's total weight judges that data matrix is
In formula: BiIndicate that the weight of i-th of index judges data matrix, bijIndicate j-th of expert to the power of i-th of index
Major punishment is broken data, that is, passes through analytic hierarchy process (AHP) gradually merger, weight of each bottom index obtained relative to destination layer
Coefficient value.
2) the deviation S for same index difference expert judgments data is found outi, determine whether to carry out weight number with this
According to amendment,
In formula:Statistical average, i=1,2 ..., n are judged for the index weights of i-th of index.
3) weight selection maximum value, which is used as, refers to weighted value, is denoted as bi0, a weight coefficient reference sequences are constituted, are
B0=[b10 b20 ... bn0]T (6)
In formula: b10=b20=...=bn0=max { bik, i=1,2 ..., n；K=1,2 ..., m.
According to formula, B is sought1, B2..., Bn, with weight coefficient reference sequences B0Between relative distance relationship, be
According to grey correlation theory, the size of relative distance reflects different experts to same index weights evaluation result
Relevance, can be in the hope of the comprehensive weight of the index after being processed to.If this distance value is smaller, show commenting for each expert
It is almost the same to sentence result, comprehensive weight can be calculated after direct standardization processing.The calculating of comprehensive weight is obtained according to relative distance
Formula are as follows:
Standardization processing is carried out to comprehensive weight, is as a result the striked final comprehensive weight coefficient of evaluation index:
Then index weights matrix is A=[ω1,...,ωi,...,ωn]。
4) when the weight sought judges data deviation value SiWhen > 0.2, i=1,2 ..., n, need to i-th index
Weight coefficient result is modified.
It is corrected by every layer weight coefficient of the consistency ratio to index a, formula is
In formula,For the weight coefficient of jth layer index corresponding to revised index a, ajIt is right for direct index a to be repaired
The weight coefficient for the jth layer index answered,For the consistency ratio of the judgment matrix of jth layer index corresponding to index a.
Each expert is to the weight coefficient of index a after then correcting
New weight coefficient is determined after amendment, deviation is then reasonable in range, with the improved grey model degree of association
Method synthesizes comprehensive weight.
In a kind of above-mentioned Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights, the step S3 is specifically wrapped
It includes:
S3-1. the data collected are standardized, specifically to the same index number of programme to be evaluated
It is standardized according to by formula (12) and formula (13), obtains the interval value of achievement data, and for substation's capacity-load ratio etc.
Achievement data can be without standardization, directly progress Fuzzy processing.
In formula: xiFor the achievement data of i-th of programme to be evaluated,For the index number of all programmes to be evaluated
According to average value.
S3-2. to treated, data carry out Fuzzy processing, obtain subordinated-degree matrix, specifically set Comment gathers as V
=(V1,V2,V3)=(is excellent, good, poor), index is divided into positive value index, negative value index and median index according to characteristic and lists person in servitude
The achievement data interval value obtained after standardization is substituted into subordinating degree function and obtains being subordinate to angle value by category degree function, is established
Subordinated-degree matrix
In formula: rijIt is i-th of index for comment VjDegree of membership, i=1,2 ..., n；J=1,2,3.
S3-3. comprehensive evaluation result is determined according to index weights matrix and subordinated-degree matrix, specifically chooses weighted average
Operator, and the scoring of each comment is set, calculate fuzzy overall evaluation result vector B=AR={ b1,b2,...,bn}。
The beneficial effects of the present invention are:
This method considers the change under electricity market reform to grid requirements, establishes adaptation electricity market reform
Indicator evaluation system, and weight determine in, it is contemplated that the entitled subjectivity of expert, with combination weights method to it is multiple specially
Family's judging result is handled, and the science and practicability of evaluation criterion weight are improved.
Detailed description of the invention
Attached drawing 1 is the flow chart of integrated evaluating method of the invention.
Attached drawing 2 is the structure chart for the indicator evaluation system established in the present invention.
Specific embodiment
With reference to the accompanying drawing, it elaborates to embodiment.
As shown in Figure 1, the specific steps of the Electric Power Network Planning fuzzy synthetic appraisement method of the invention based on combination weights are such as
Under:
S1. the Electric Power Network Planning indicator evaluation system for adapting to electricity market reform is established.And the following steps are included:
S1-1. according to electricity market reform the characteristics of, the index of screening reliability, economy and Environmental three aspect；
According to the purpose of Electric Power Network Planning overall merit, and combine new energy rapid development, electricity price after electricity market reform
Electric Power Network Planning Comprehensive Evaluation Problem is resolved into reliability, economy and Environmental three aspects, screening by the features such as mechanism changes
The evaluation index of this three aspect, and determine the hierarchical structure between each index, finally obtain an adaptation electricity market reform
Electric Power Network Planning indicator evaluation system, hierarchical chart is as shown in Figure 2.
S1-2. the definition and calculation method of clear index, establishes indicator evaluation system.
S2. each index weights in index system are determined based on combination weights method.And the following steps are included:
S2-1. multiple expert opinions are acquired；
The interior multidigit authoritative expert that chooses a trade carries out weight judgement, and every expert writes judgment matrix by column and directly assigns power
Mode determine index weights.For the upper layer index of the next layer of index containing there are three or more, write using Satty rule column
Judgment matrix, for containing there are two and lower layer's index below upper layer index, selection directly entitled method column write assignment to
Amount.
In formula: U1, U2, U3Reliability in assessment indicator system, economy and Environmental three first class index are referred respectively to,
aijFor first class index UiAnd UjFor the judgement numerical value of the significance level of entire evaluation goal.
In formula: U21And U22Refer respectively to the input-occupancy-output analysis and output index under economic index, ciFor economic index institute
Including two-level index U2iThe ratio accounted in economic index, and meet c1+c2=1.
S2-2. the weight judging result for merging and obtaining each expert is calculated；
The weight vectors of each judgment matrix are calculated, and carry out consistency judgement, it is every according to the layer-by-layer merger of analytic hierarchy process (AHP)
The weight vectors and adele of a expert, synthesis obtain the weight judging result of each expert.It is acquired according to judgment matrix A
Rule layer in n factor for destination layer weight coefficient be α=(α1,α2,...,αi,...,αn)T, i-th of rule layer because
The lower l of elementiA index is for the weight coefficient of this criterionThe then index under the rule layer factor
Weight coefficient for destination layer isThen all index factors for
Total weight coefficient of destination layer, the i.e. total weight of single human expert judge that data are
γ=(γ1,γ2,...,γn)T=(α1β1,α2β2,...,αnβn)T (3)
S2-3. according to improved Gray Correlation synthetic population comprehensive weight, index weights matrix is obtained.
1) there is n lowest level index in assessment indicator system, there is m expert to judge these index weights, then
Expert's total weight judges that data matrix is
In formula: BiIndicate that the weight of i-th of index judges data matrix, bijIndicate j-th of expert to the power of i-th of index
Major punishment is broken data, that is, passes through analytic hierarchy process (AHP) gradually merger, weight of each bottom index obtained relative to destination layer
Coefficient value.
2) the deviation S for same index difference expert judgments data is found outi, determine whether to carry out weight number with this
According to amendment,
In formula:Statistical average, i=1,2 ..., n are judged for the index weights of i-th of index.
3) weight selection maximum value, which is used as, refers to weighted value, is denoted as bi0, a weight coefficient reference sequences are constituted, are
B0=[b10 b20 ... bn0]T (6)
In formula: b10=b20=...=bn0=max { bik, i=1,2 ..., n；K=1,2 ..., m.
According to formula, B is sought1, B2..., Bn, with weight coefficient reference sequences B0Between relative distance relationship, be
According to grey correlation theory, the size of relative distance reflects different experts to same index weights evaluation result
Relevance, can be in the hope of the comprehensive weight of the index after being processed to.If this distance value is smaller, show commenting for each expert
It is almost the same to sentence result, comprehensive weight can be calculated after direct standardization processing.The calculating of comprehensive weight is obtained according to relative distance
Formula are as follows:
Standardization processing is carried out to comprehensive weight, is as a result the striked final comprehensive weight coefficient of evaluation index:
Then index weights matrix is A=[ω1,...,ωi,...,ωn]。
4) when the weight sought judges data deviation value SiWhen > 0.2, i=1,2 ..., n, need to i-th index
Weight coefficient result is modified.
It is corrected by every layer weight coefficient of the consistency ratio to index a, formula is
In formula,For the weight coefficient of jth layer index corresponding to revised index a, ajIt is right for direct index a to be repaired
The weight coefficient for the jth layer index answered,For the consistency ratio of the judgment matrix of jth layer index corresponding to index a.
Each expert is to the weight coefficient of index a after then correcting
New weight coefficient is determined after amendment, deviation is then reasonable in range, with the improved grey model degree of association
Method synthesizes comprehensive weight
S3. each achievement data for handling programme to be evaluated is collected, Electric Power Network Planning model of fuzzy synthetic evaluation is established.Again
The following steps are included:
S3-1. the data collected are standardized；
The same achievement data of programme to be evaluated is standardized by formula (12) and formula (13), is referred to
The interval value of data is marked, and the achievement datas such as substation's capacity-load ratio can be directly blurred without standardization
Processing.
In formula: xiFor the achievement data of i-th of programme to be evaluated,For the index number of all programmes to be evaluated
According to average value.
S3-2. to treated, data carry out Fuzzy processing, obtain subordinated-degree matrix；
Comment gathers are set as V=(V1,V2,V3)=(is excellent, good, poor), index is divided into positive value index, negative value according to characteristic
Index and median index list subordinating degree function, and the achievement data interval value obtained after standardization is substituted into degree of membership letter
It obtains being subordinate to angle value in number, establishes subordinated-degree matrix
In formula: rijIt is i-th of index for comment VjDegree of membership, i=1,2 ..., n；J=1,2,3.
S3-3. comprehensive evaluation result is determined according to index weights matrix and subordinated-degree matrix.
Weighted average operator is chosen, and sets the scoring of each comment, calculates fuzzy overall evaluation result vector B=AR
={ b1,b2,...,bn}。
Above-mentioned, although specific embodiments of the present invention have been described, not to the limit of the scope of the present invention
System, the technological development personnel of fields are it is to be appreciated that based on the technical solutions of the present invention, this field and related fields
Technical staff do not need to make the creative labor the various modifications or changes that can be made, still protection scope of the present invention with
It is interior.
Claims (4)
1. a kind of Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights, which comprises the steps of:
S1. the Electric Power Network Planning indicator evaluation system for adapting to electricity market reform is established；
S2. each index weights in index system are determined based on combination weights method；
S3. each achievement data for handling programme to be evaluated is collected, Electric Power Network Planning model of fuzzy synthetic evaluation is established.
2. a kind of Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights according to claim 1, feature exist
In the step S1 is specifically included:
S1-1. according to electricity market reform the characteristics of, the index of screening reliability, economy and Environmental three aspect；
S1-2. the definition and calculation method of clear index, establishes indicator evaluation system.
3. a kind of Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights according to claim 1, feature exist
In the step S2 is specifically included:
S2-1. multiple expert judgments are acquired as a result, being specifically:
The interior multidigit authoritative expert that chooses a trade carries out weight judgement, and every expert writes judgment matrix and direct entitled side by column
Formula determines index weights；For the upper layer index of the next layer of index containing there are three or more, judgement is write using Satty rule column
Matrix, for containing there are two and lower layer's index below upper layer index, selection directly entitled method column write adele；
In formula: U1, U2, U3Refer respectively to reliability in assessment indicator system, economy and Environmental three first class index, aijFor
First class index UiAnd UjFor the judgement numerical value of the significance level of entire evaluation goal；
In formula: U21And U22Refer respectively to the input-occupancy-output analysis and output index under economic index, ciFor included by economic index
Two-level index U2iThe ratio accounted in economic index, and meet c1+c2=1；
S2-2. the weight judging result for merging and obtaining each expert is calculated, the weight vectors of each judgment matrix are specifically calculated,
And consistency judgement is carried out, according to the weight vectors and adele of each expert of the layer-by-layer merger of analytic hierarchy process (AHP), synthesis is obtained
The weight judging result of each expert；According to n factor in the obtained rule layer of judgment matrix A for the weight system of destination layer
Number is α=(α1,α2,...,αi,...,αn)T, l under i-th of rule layer factoriA index is for the weight coefficient of this criterion
β=(βi1,βi2,...,βili)T, then the index under the rule layer factor is γ for the weight coefficient of destination layeri=αiβi=(αi
βi1,αiβi2,...,αiβili)T, i=1,2 ..., n；Then all index factors for destination layer total weight coefficient, i.e., individually
The total weight of expert judges that data are
γ=(γ1,γ2,...,γn)T=(α1β1,α2β2,...,αnβn)T (3)
S2-3. according to improved Gray Correlation synthetic population comprehensive weight, index weights matrix is obtained, is specifically included
1) there is n lowest level index in assessment indicator system, there is m expert to judge these index weights, then expert
Total weight judges that data matrix is
In formula: BiIndicate that the weight of i-th of index judges data matrix, bijIndicate that j-th of expert sentences the weight of i-th of index
Disconnected data, that is, pass through analytic hierarchy process (AHP) gradually merger, weight coefficient of each bottom index obtained relative to destination layer
Value；
2) the deviation S for same index difference expert judgments data is found outi, determine whether to carry out weighted data with this
Amendment,
In formula:Statistical average, i=1,2 ..., n are judged for the index weights of i-th of index；
3) weight selection maximum value, which is used as, refers to weighted value, is denoted as bi0, a weight coefficient reference sequences are constituted, are
B0=[b10 b20...bn0]T (6)
In formula: b10=b20=...=bn0=max { bik, i=1,2 ..., n；K=1,2 ..., m；
According to formula, B is sought1, B2..., Bn, with weight coefficient reference sequences B0Between relative distance relationship, be
According to grey correlation theory, the size of relative distance reflects association of the different experts to same index weights evaluation result
Property, it can be in the hope of the comprehensive weight of the index after being processed to；If this distance value is smaller, show the judge knot of each expert
Fruit is almost the same, can calculate comprehensive weight after direct standardization processing；The calculation formula of comprehensive weight is obtained according to relative distance
Are as follows:
Standardization processing is carried out to comprehensive weight, is as a result the striked final comprehensive weight coefficient of evaluation index:
Then index weights matrix is A=[ω1,...,ωi,...,ωn]；
4) when the weight sought judges data deviation value SiWhen > 0.2, i=1,2 ..., n, the weight system to i-th of index is needed
Number result is modified；
It is corrected by every layer weight coefficient of the consistency ratio to index a, formula is
In formula,For the weight coefficient of jth layer index corresponding to revised index a, ajFor corresponding to direct index a to be repaired
The weight coefficient of jth layer index,For the consistency ratio of the judgment matrix of jth layer index corresponding to index a；
Each expert is to the weight coefficient of index a after then correcting
New weight coefficient is determined after amendment, deviation is then reasonable in range, closes with improved grey model degree of association method
At comprehensive weight.
4. a kind of Electric Power Network Planning fuzzy synthetic appraisement method based on combination weights according to claim 1, feature exist
In the step S3 is specifically included:
S3-1. the data collected are standardized, it is specifically logical to the same achievement data of programme to be evaluated
It crosses formula (12) and formula (13) is standardized, obtain the interval value of achievement data, and for indexs such as substation's capacity-load ratios
Data can be without standardization, directly progress Fuzzy processing；
In formula: xiFor the achievement data of i-th of programme to be evaluated,It is flat for the achievement data of all programmes to be evaluated
Mean value；
S3-2. to treated, data carry out Fuzzy processing, obtain subordinated-degree matrix, specifically set Comment gathers as V=(V1,
V2,V3)=(is excellent, good, poor), index is divided into positive value index, negative value index and median index according to characteristic and lists degree of membership letter
The achievement data interval value obtained after standardization is substituted into subordinating degree function and obtains being subordinate to angle value, establishes degree of membership by number
Matrix
In formula: rijIt is i-th of index for comment VjDegree of membership, i=1,2 ..., n；J=1,2,3；
S3-3. comprehensive evaluation result is determined according to index weights matrix and subordinated-degree matrix, specifically chooses weighted average operator,
And the scoring of each comment is set, calculate fuzzy overall evaluation result vector B=AR={ b1,b2,...,bn}。
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Application publication date: 20190521 |