CN109858758A - A kind of the combination weighting appraisal procedure and system of distribution network electric energy quality - Google Patents
A kind of the combination weighting appraisal procedure and system of distribution network electric energy quality Download PDFInfo
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Abstract
The present invention relates to the combination weighting appraisal procedure and system of a kind of distribution network electric energy quality, advanced AHP method is respectively adopted and improves subjective weight and objective weight that entropy assessment determines power quality index；Comprehensive assessment is carried out to master, objective weight by the Evaluation formula of maximum variance, obtains Comprehensive assessment of power quality value result.Above scheme had not only considered the weight that the preference of policymaker obtains by Objective Weight and subjective weights combination weighting mode, but also ensure that the objectivity of decision to a certain extent；And maximum variance thought is combined, each scheme evaluation of estimate made in a manner of combination weighting is more discrete, is conducive to policymaker and more clearly makes relevant Decision.
Description
Technical field
The present invention relates to power station data technical field of memory, and in particular to a kind of combination weighting of distribution network electric energy quality is commented
Estimate method and system.
Background technique
With the construction of smart grid, the scale of power grid is more come more greatly, and the researchs such as smart grid, intelligent substation application is not
Disconnected to go deep into, the collection point that system faces is more and more, and the collection capacity in the previous medium-scale area of mesh can achieve 2 ten thousand to 10
Ten thousand, and one adjust large-scalely it is following may face 500,000 to 1,000,000 data acquisition scale, 1 year data according to a preliminary estimate will be from
Current gigabyte grade turns to terabyte grade；In addition, proposing real time execution number with the continuous improvement of dispatching automation level
According to requirement, do not use periodic samples to store but according to the requirements at the higher level that actual run time Sequentially continuous stores, with full
The more application demands of foot, this also leads to substation as data acquisition sources head, the growth of data storage size decades of times, with
The expansion of data scale so that storage system needs constantly dynamic to expand storage size, and storage system allows for propping up
It holds new memory node to be continuously added, guarantees data being uniformly distributed in each memory node, therefore, to data storage technology
It is required that also increasing accordingly.
Current power grid in collected data set using will be deployed in single node storage equipment, with data scale
Expand, it will cause the resource (such as memory, magnetic disc i/o) of separate unit host not to be able to satisfy magnanimity grade data requirements, it is necessary to subsequent
Dilatation, however dilatation cost is very expensive, causes largely to store in addition, will lead to when the additions and deletions of server memory node or delay machine
Data relocate, inefficiency；Traditional hash algorithm is generallyd use in existing distributed storage technology or consistency is breathed out
Uncommon algorithm is used for the fragment of mass data, for traditional hash algorithm, the mapping position of all data objects of additions and deletions memory node
The problem of recalculating, mass data is caused to relocate is needed, for consistency hash algorithm, if memory node is less
Words, data object can not be uniformly mapped on memory node, will cause the unbalanced problem of data distribution.
Summary of the invention
In order to overcome above-mentioned deficiency, objectivity, the science of Comprehensive assessment of power quality are improved, the present invention provides one kind and matches
The combination weighting appraisal procedure and system of grid power quality, the Evaluation formula that subjective weighting method is combined with objective weighted model
To determine the weight of each technical index of power quality.Subjective weight and objective weight are combined, ginseng can be effectively reacted
With the subjective desire of person, and the excessive randomness of subjective factor can avoid, index weights can occur with the variation of data
Variation, entitled result are more reasonable.
The purpose of the present invention is adopt the following technical solutions realization:
A kind of combination weighting appraisal procedure of distribution network electric energy quality, which comprises
Advanced AHP method is respectively adopted and improves subjective weight and objective weight that entropy assessment determines power quality index；
Comprehensive assessment is carried out to master, objective weight by the Evaluation formula of maximum variance, obtains comprehensive power quality
Evaluation of estimate result.
Preferably, the subjective weight using advanced AHP method power quality evaluation index includes:
Power quality evaluation index is determined according to the Analysis of Hierarchy Structure model level pre-established；
Using the relative importance for improving more adjacent two indexs of scaling law, consistency matrix is established；
The consistency matrix is solved, the subjective weight of each power quality evaluation index is obtained.
Further, the level of the Analysis of Hierarchy Structure model includes: destination layer, accurate layer and solution layer；Wherein,
The destination layer is used to determine the property and target of evaluation index；
The accurate layer is for defining power quality evaluation index type；Including technical/inartful index；
The solution layer is used to store the concrete scheme of each power quality evaluation index；
The power quality evaluation index includes three-phase imbalance, voltage dip, voltage deviation, harmonic wave, voltage fluctuation, frequency
Rate deviation, flickering and user satisfaction.
Further, the consistency matrix is established by following formula:
In formula, r indicates the evaluation of estimate of power quality evaluation index, and n is power quality evaluation index number, tnFor scale
Value, tn=rn/rn+1。
Further, the subjective weight of each power quality evaluation index is determined by following formula:
U=(u1,u2,…,un)
In formula, U is the subjective weight of each power quality evaluation index, uiFor the subjective weight of i-th of evaluation index, i=
1,2,…,n；N is power quality evaluation index number；rijIndicate assessment object set S={ S1,S2,…,SmIn i-th assessment pair
As SiEvaluation of estimate in j-th of power quality evaluation index.
Preferably, the objective weight that power quality evaluation index is determined using improvement entropy assessment includes:
The assessment object set that operation data based on power grid is constituted chooses corresponding power quality evaluation index, building evaluation
Matrix；
Each power quality evaluation index is defined to the feature specific gravity of the evaluations matrix, and calculates the information of each evaluation index
Entropy；
By comentropy after improving, the entropy weight of each power quality evaluation index is calculated；
Based on the entropy weight, the objective weight of each power quality evaluation index is determined.
Further, evaluations matrix is determined by following formula:
R=(rij)m×n
In formula, rijIndicate assessment object set S={ S1,S2,…,SmIn i-th of evaluation object SiIn j-th of power quality
Evaluation of estimate in evaluation index；I=1,2 ..., m, j=1,2 ..., n；N is power quality evaluation index number；M is assessment pair
As the evaluation object number of concentration.
Further, determine power quality evaluation index to the feature specific gravity of evaluations matrix by following formula:
In formula, pijTo assess object S for power quality evaluation indexiFeature specific gravity, rij *For each evaluation of estimate process
The value obtained after standardization, and 0≤rij *≤1；
Further, the comentropy of power quality evaluation index is determined by following formula:
In formula, if pij=0, then enable lnpij=0, HjIndicate the comentropy for j-th of the power quality evaluation index chosen.
Further, the objective weight of each power quality evaluation index is determined by following formula:
V=(v1,v2,…,vn)
In formula, ε is adjustment item, vjFor the objective weight of j-th of power quality evaluation index, V is that every power quality is commented
Estimate the objective weight of index, HjFor the entropy weight of j-th of evaluation index.
Preferably, the Evaluation formula by maximum variance carries out comprehensive assessment to master, objective weight, obtains electricity
Can quality overall evaluation value result include:
Master, objective weight based on power quality evaluation index define the weight vectors of power quality evaluation index；
Using the weight vectors maximum variance of power quality evaluation index as target, linear programming model is constructed, and define
The Lagrangian of the majority linear programming model；
Parameter optimization is carried out to the Lagrangian, to obtain the optimization solution of linear programming model；
Optimize the set weight of solution described in normalized, obtains Comprehensive assessment of power quality value result.
Further, the weight vectors of power quality evaluation index are determined by following formula:
ω=α U+ β V；
In formula, weight vectors ω=(ω of power quality evaluation index1,ω2,…,ωn)τ, ωnFor n-th of power quality
The weight vectors of evaluation index, α, β be right vector linear expression coefficient, α >=0, β >=0, and α, β meet it is unitization about
Beam condition α2+β2=1；U is subjective weight, and V is objective weight.
Further, linear programming model is determined by following formula:
s.t.α2+β2=1
α, β > 0
In formula, Z is the weight vectors variance of power quality evaluation index, and α, β are the linear expression coefficient of right vector,
rijIndicate assessment object set S={ S1,S2,…,SmIn i-th of evaluation object SiCommenting in j-th of power quality evaluation index
Value；ujFor the subjective weight of j-th of evaluation index, vjFor the objective weight of j-th of evaluation index, ωjFor j-th of electric energy matter
The weight vectors of evaluation index are measured, Indicate the arithmetic average of the m attribute value of attribute i
Value.
Further, the Lagrangian of most linear programming models is determined by following formula:
It enables,Have:
In formula, L is the Lagrangian of most linear programming models, and λ is Lagrange multiplier.
Further, by following formula to the set weight of the optimization solution of the linear programming model:
α2+β2=1, ω=α U+ β V, ω=(ω1,ω2,…,ωn)τ。
Further, the set weight for optimizing solution described in normalized is determined by following formula:
ω0=(ω01,ω02,…,ω0n)τ。
Further, Comprehensive assessment of power quality value result is determined by following formula:
A kind of combination weighting assessment system of distribution network electric energy quality, the system comprises:
First determining module, for determining the subjective weight of power quality evaluation index using advanced AHP method；
Second determining module, for determining the objective weight of power quality evaluation index using improvement entropy assessment；
Evaluation module carries out comprehensive assessment to master, objective weight for the Evaluation formula by maximum variance, obtains
Comprehensive assessment of power quality value result.
Compared with the immediate prior art, the present invention is also had the following beneficial effects:
A kind of the combination weighting appraisal procedure and system of distribution network electric energy quality, firstly, advanced AHP method is respectively adopted and changes
The subjective weight and objective weight of power quality index are determined into entropy assessment；Subjective weight and objective weight are combined, it can
The obtained weight of preference for considering policymaker effectively reacts the subjective desire of participant, and it is excessive to can avoid subjective factor
Randomness ensure that the objectivity of decision to a certain extent；Index weights are become with the variation of data
Change, entitled result is more reasonable.Wherein, the subjective weight of power quality indexes is obtained using advanced AHP method, do not needed pair
Judgment matrix carries out consistency check, calculates easier；And it uses and improves the available power quality indexes of entropy assessment
Objective weight, solve traditional entropy assessment when entropy tends to 1, the problem of index weights inaccuracy.
Secondly, the Evaluation formula by maximum variance carries out comprehensive assessment to master, objective weight, power quality is obtained
Comprehensive evaluation value result.On the basis of subjective weight and objective weight, using the Evaluation formula based on maximum variance, obtain
The thought that maximum variance is combined to the inventive technique scheme of the index of electric energy quality synthesis evaluation, is made in a manner of combination weighting
Obtained each scheme evaluation of estimate is more discrete, is conducive to policymaker and more clearly makes relevant Decision.
Detailed description of the invention
Fig. 1 is the flow chart of the combination weighting appraisal procedure of the distribution network electric energy quality provided in the embodiment of the present invention；
Fig. 2 has been the modified AHP flow chart provided in the embodiment of the present invention；
Fig. 3 is the electric energy quality synthesis evaluation index system schematic diagram provided in the embodiment of the present invention；
Fig. 4 is the improvement entropy weight method flow diagram provided in the embodiment of the present invention.
Specific embodiment
It elaborates with reference to the accompanying drawing to a specific embodiment of the invention.
Progress rationally objective comprehensive assessment to power quality is to realize quality supply, improve national economy benefit
Basis.Power quality is a multi-index cluster zoarium, therefore, only qualitative to point out each finger in electric energy quality synthesis evaluation
Target importance is inadequate, it is necessary to make its quantization and accurate.Since the weight of each evaluation index of power quality is commented as synthesis
The key of valence, the value of weight will directly affect the scientific rationality of power quality evaluation result.The present invention is intended to provide one
Kind comprehensively considers subjective weight and objective weight, and uses the Evaluation formula based on maximum variance, to each of power quality
Item index carries out comprehensive assessment, improves the accuracy of electric energy quality synthesis evaluation result.
The present invention comprehensively considers two aspect of technical index and inartful index of power quality problem, establishes electric energy matter
Measure comprehensive assessment index system.It is processed into decision-making problem of multi-objective according to the characteristics of electricity quality evaluation, by improvement layer
Fractional analysis (The Analytic Hierarchy Process, referred to as AHP method) and improvement entropy assessment determine indices
Master, objective weight, and the comprehensive weight of power quality is determined using maximum variance principle on this basis, thus for electricity
The comprehensive assessment of energy quality provides a kind of new method.
As shown in Figure 1, in the embodiment of the present invention combination weighting appraisal procedure of distribution network electric energy quality flow chart, use
A kind of combination weighting method based on maximum variance, objective weight and subjective weight to obtained power quality index carry out
Comprehensive assessment；Specific step is as follows for the method:
S1 is respectively adopted advanced AHP method and improves subjective weight and objective weight that entropy assessment determines power quality index；
S2 carries out comprehensive assessment to master, objective weight by the Evaluation formula of maximum variance, and it is comprehensive to obtain power quality
Close evaluation of estimate result.
Step S1: as shown in Fig. 2, determining the subjective weight of power quality evaluation index using advanced AHP method；
AHP method will make respectively destination layer, rule layer and solution layer according to the property and target of problem, such as Fig. 3 institute
Show.Evaluation index one shares 8, including three-phase imbalance, voltage dip, voltage deviation, harmonic wave, voltage fluctuation, frequency departure,
Flickering and user satisfaction.
Traditional AHP method need to need to carry out consistency check to judgment matrix, work as judgment matrix when establishing judgment matrix
When not being able to satisfy consistency check, it is necessary to correct judgment matrix again, until meeting consistency, calculation amount is very big.This
Invention uses a kind of improved method of AHP, the i.e. Scale-Extending of AHP, has all been using the judgment matrix that this method determines
It is complete consistent, do not need consistency check, and ordering vector is also easy to get, calculation amount significantly reduces, method is easy, it is intuitive just
In use.
Improved AHP method basic ideas: according to an expert view or user requires to compare 8 evaluation indexes two-by-two
Compared with sorting by the mode that do not subtract of significance level, it is assumed that according to the importance ranking that Scale-Extending obtains 8 indexs be x1≥x2
≥…xn, to xiWith xi+1It is compared, and its corresponding scale value is denoted as ti, then according to the transitivity of index significance level
The value of the other elements in judgment matrix is calculated, to obtain judgment matrix R.Scale value and meaning are shown in Table 1.
1 scale value of table and meaning
In formula, r indicates the evaluation of estimate of power quality evaluation index, and n is power quality evaluation index number, tnFor scale
Value, tn=rn/rn+1。
In embodiment, enabling as power quality evaluation index number is 8, then:
Thus the judgment matrix obtained is with uniformity, therefore does not need to carry out consistency check, can be directly according to square
Battle array R calculates the weighted value of indices:
Wherein, uiFor the subjective weight of i-th of index, i=1,2 ..., 8.
Finally, the subjective weight for obtaining each evaluation index of power quality is U, U=(u1,u2,…,u8)。
2, as shown in figure 4, determining the objective weight of power quality evaluation index using improvement entropy assessment；
A: the assessment object set that the operation data based on power grid is constituted chooses corresponding power quality evaluation index, and building is commented
Valence matrix
R=(rij)m×n；
If assessing object set S={ S1,S2,…,Sm}；Correlative factor, that is, evaluation index collection F={ f1,f2,…,fn}。
Wherein, rijIndicate evaluation object SiIn index fjOn evaluation of estimate；rij *Pass through standardization for each evaluation of estimate
The value obtained afterwards, and 0≤rij *≤ 1, i=1,2 ..., m, j=1,2 ..., 8；f1For tri-phase unbalance factor, f2For voltage dip,
f3For voltage dip, f4For harmonic wave, f5For voltage fluctuation, f6For frequency departure, f7For flickering, f8For user satisfaction.
B: each evaluation index is calculated to the feature specific gravity matrix P of each evaluating matrix, and calculates the comentropy H of each indexj；
For index fj, assess object SiFeature specific gravity are as follows:
Index fjEntropy are as follows:
In formula, if pij=0, then enable ln pij=0.
C: the entropy weight of each evaluation index is calculated using following improvement entropy assessment formula；
Wherein, ε is adjustment item, usually desirable 0.01, j=1,2 ..., n；
vjFor the objective weight of j-th of index；
HjFor entropy.
D: the power quality objective weight of each evaluation index is calculated using improved entropy weight.
By calculating, the objective weight for obtaining power quality items evaluation index is V, V=(v1,v2,…,vn)。
After executing step S2, the weight vectors of power quality evaluation index are established；
The linear combination of two kinds of weights is expressed as integrated power by the characteristics of in order to integrate two methods of subjective and Objective Weight
Weight ω=α U+ β V.
Wherein, ω=(ω1,ω2,…,ωn)τ；
The linear expression coefficient of α, β for right vector, α >=0, β >=0, and α, β meet unitization constraint condition α2+β2=
1；U is subjective weight；V is objective weight.
Step S2: with the Evaluation formula based on maximum variance, comprehensive assessment is carried out to power quality.
Variance is to reflect an important indicator of difference degree in statistics.Thought based on maximum variance, weight to
Measure ω=(ω1,ω2,…,ωn)τAll n attributes should be made to reach maximum to the population variance of all m decision schemes.By
This can construct following linear programming model:
s.t.α2+β2=1
α, β > 0
In model,The arithmetic mean of instantaneous value for indicating the m attribute value of attribute i, that is, have
In order to solve above-mentioned optimization problem, it is as follows Lagrangian can be constructed:
Wherein, λ is Lagrange multiplier.
It enables:Have:
There is α again2+β2=1, as follows so as to value that α, β is calculated:
In the case where obtaining α, β value, and then available integrated weights omega=α U+ β V, then to ω=(ω1,
ω2,…,ωn)τIt is normalized, the result ω after being normalized0=(ω01,ω02,…,ω0n)τAs each category
The final weight of property.Comprehensive evaluation value result based on the available each scheme of the weights:
Based on the same inventive concept, the application also proposes a kind of combination weighting assessment system of distribution network electric energy quality, institute
The system of stating includes:
First determining module, for determining the subjective weight of power quality evaluation index using advanced AHP method；
Second determining module, for determining the objective weight of power quality evaluation index using improvement entropy assessment；
Evaluation module carries out comprehensive assessment to master, objective weight for the Evaluation formula by maximum variance, obtains
Comprehensive assessment of power quality value result.
It should be understood by those skilled in the art that, embodiments herein can provide as method, system or computer program
Product.Therefore, complete hardware embodiment, complete software embodiment or reality combining software and hardware aspects can be used in the application
Apply the form of example.Moreover, it wherein includes the computer of computer usable program code that the application, which can be used in one or more,
The computer program implemented in usable storage medium (including but not limited to magnetic disk storage, CD-ROM, optical memory etc.) produces
The form of product.
The application is referring to method, the process of equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram describe.It should be understood that every one stream in flowchart and/or the block diagram can be realized by computer program instructions
The combination of process and/or box in journey and/or box and flowchart and/or the block diagram.It can provide these computer programs
Instruct the processor of general purpose computer, special purpose computer, Embedded Processor or other programmable data processing devices to produce
A raw machine, so that being generated by the instruction that computer or the processor of other programmable data processing devices execute for real
The device for the function of being specified in present one or more flows of the flowchart and/or one or more blocks of the block diagram.
These computer program instructions, which may also be stored in, is able to guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works, so that it includes referring to that instruction stored in the computer readable memory, which generates,
Enable the manufacture of device, the command device realize in one box of one or more flows of the flowchart and/or block diagram or
The function of being specified in multiple boxes.
These computer program instructions also can be loaded onto a computer or other programmable data processing device, so that counting
Series of operation steps are executed on calculation machine or other programmable devices to generate computer implemented processing, thus in computer or
The instruction executed on other programmable devices is provided for realizing in one or more flows of the flowchart and/or block diagram one
The step of function of being specified in a box or multiple boxes.
Finally it should be noted that: the above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, to the greatest extent
Invention is explained in detail referring to above-described embodiment for pipe, it should be understood by those ordinary skilled in the art that: still
It can be with modifications or equivalent substitutions are made to specific embodiments of the invention, and without departing from any of spirit and scope of the invention
Modification or equivalent replacement, should all cover within the scope of the claims of the present invention.
Claims (18)
1. a kind of combination weighting appraisal procedure of distribution network electric energy quality, which is characterized in that the described method includes:
Advanced AHP method is respectively adopted and improves subjective weight and objective weight that entropy assessment determines power quality index；
Comprehensive assessment is carried out to master, objective weight by the Evaluation formula of maximum variance, obtains Comprehensive assessment of power quality
It is worth result.
2. the method as described in claim 1, which is characterized in that the master using advanced AHP method power quality evaluation index
Seeing weight includes:
Power quality evaluation index is determined according to the Analysis of Hierarchy Structure model level pre-established；
Using the relative importance for improving more adjacent two indexs of scaling law, consistency matrix is established；
The consistency matrix is solved, the subjective weight of each power quality evaluation index is obtained.
3. method according to claim 2, which is characterized in that the level of the Analysis of Hierarchy Structure model include: destination layer,
Accurate layer and solution layer；Wherein,
The destination layer is used to determine the property and target of evaluation index；
The accurate layer is for defining power quality evaluation index type；Including technical/inartful index；
The solution layer is used to store the concrete scheme of each power quality evaluation index；
The power quality evaluation index includes that three-phase imbalance, voltage dip, voltage deviation, harmonic wave, voltage fluctuation, frequency are inclined
Difference, flickering and user satisfaction.
4. method according to claim 2, which is characterized in that the consistency matrix is established by following formula:
In formula, r indicates the evaluation of estimate of power quality evaluation index, and n is power quality evaluation index number, tnFor scale value, tn=
rn/rn+1。
5. method as claimed in claim 4, which is characterized in that determine that the subjective of each power quality evaluation index is weighed by following formula
Weight:
U=(u1,u2,…,un)
In formula, U is the subjective weight of each power quality evaluation index, uiFor the subjective weight of i-th of evaluation index, i=1,
2,…,n；N is power quality evaluation index number；rijIndicate assessment object set S={ S1,S2,…,SmIn i-th of assessment object
SiEvaluation of estimate in j-th of power quality evaluation index.
6. the method as described in claim 1, which is characterized in that described to determine power quality evaluation index using improvement entropy assessment
Objective weight include:
The assessment object set that operation data based on power grid is constituted chooses corresponding power quality evaluation index, building evaluation square
Battle array；
Each power quality evaluation index is defined to the feature specific gravity of the evaluations matrix, and calculates the comentropy of each evaluation index；
By comentropy after improving, the entropy weight of each power quality evaluation index is calculated；
Based on the entropy weight, the objective weight of each power quality evaluation index is determined.
7. method as claimed in claim 6, which is characterized in that determine evaluations matrix by following formula:
R=(rij)m×n
In formula, rijIndicate assessment object set S={ S1,S2,…,SmIn i-th of evaluation object SiIt is evaluated in j-th of power quality
Evaluation of estimate in index；I=1,2 ..., m, j=1,2 ..., n；N is power quality evaluation index number；M is assessment object set
In evaluation object number.
8. the method for claim 7, which is characterized in that determine power quality evaluation index to evaluations matrix by following formula
Feature specific gravity:
In formula, pijTo assess object S for power quality evaluation indexiFeature specific gravity, rij *Pass through standard for each evaluation of estimate
The value obtained after change processing, and 0≤rij *≤1。
9. method as claimed in claim 6, which is characterized in that determine the comentropy of power quality evaluation index by following formula:
In formula, if pij=0, then enable lnpij=0, HjIndicate the comentropy for j-th of the power quality evaluation index chosen.
10. method as claimed in claim 9, which is characterized in that determine the objective of each power quality evaluation index by following formula
Weight:
V=(v1,v2,…,vn)
In formula, ε is adjustment item, vjFor the objective weight of j-th of power quality evaluation index, V is every electricity quality evaluation index
Objective weight, HjFor the entropy weight of j-th of evaluation index.
11. the method as described in claim 1, which is characterized in that the Evaluation formula by maximum variance is to master, visitor
It sees weight and carries out comprehensive assessment, obtaining Comprehensive assessment of power quality value result includes:
Master, objective weight based on power quality evaluation index define the weight vectors of power quality evaluation index；
Using the weight vectors maximum variance of power quality evaluation index as target, linear programming model is constructed, and described in definition
The Lagrangian of most linear programming models；
Parameter optimization is carried out to the Lagrangian, to obtain the optimization solution of linear programming model；
Optimize the set weight of solution described in normalized, obtains Comprehensive assessment of power quality value result.
12. method as claimed in claim 11, which is characterized in that by following formula determine the weight of power quality evaluation index to
Amount:
ω=α U+ β V；
In formula, weight vectors ω=(ω of power quality evaluation index1,ω2,…,ωn)τ, ωnIt is evaluated for n-th of power quality
The weight vectors of index, the linear expression coefficient of α, β for right vector, α >=0, β >=0, and α, β meet unitization constraint item
Part α2+β2=1；U is subjective weight, and V is objective weight.
13. method as claimed in claim 12, which is characterized in that determine linear programming model by following formula:
s.t.α2+β2=1
α, β > 0
In formula, Z is the weight vectors variance of power quality evaluation index, and α, β are the linear expression coefficient of right vector, rijTable
Show assessment object set S={ S1,S2,…,SmIn i-th of evaluation object SiEvaluation in j-th of power quality evaluation index
Value；ujFor the subjective weight of j-th of evaluation index, vjFor the objective weight of j-th of evaluation index, ωjFor j-th of power quality
The weight vectors of evaluation index, Indicate the arithmetic mean of instantaneous value of the m attribute value of attribute i.
14. method as claimed in claim 13, which is characterized in that determine that the glug of most linear programming models is bright by following formula
Day function:
It enables,Have:
In formula, L is the Lagrangian of most linear programming models, and λ is Lagrange multiplier.
15. method as claimed in claim 14, which is characterized in that solved by following formula to the optimization of the linear programming model
Gather weight:
α2+β2=1, ω=α U+ β V, ω=(ω1,ω2,…,ωn)τ。
16. method as claimed in claim 15, which is characterized in that determine the collection for optimizing solution described in normalized by following formula
Close weight:
ω0=(ω01,ω02,…,ω0n)τ。
17. the method described in claim 16, which is characterized in that determine Comprehensive assessment of power quality value result by following formula:
18. a kind of combination weighting assessment system of distribution network electric energy quality, which is characterized in that the system comprises:
First determining module, for determining the subjective weight of power quality evaluation index using advanced AHP method；
Second determining module, for determining the objective weight of power quality evaluation index using improvement entropy assessment；
Evaluation module carries out comprehensive assessment to master, objective weight for the Evaluation formula by maximum variance, obtains electric energy
Quality overall evaluation value result.
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
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Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109003000A (en) * | 2018-04-10 | 2018-12-14 | 华侨大学 | A kind of energy quality comprehensive assessment method of active distribution network |
-
2018
- 2018-12-29 CN CN201811632904.0A patent/CN109858758A/en active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109003000A (en) * | 2018-04-10 | 2018-12-14 | 华侨大学 | A kind of energy quality comprehensive assessment method of active distribution network |
Non-Patent Citations (3)
| Title |
|---|
| 孙莹等: "一种基于方差最大化的组合赋权评价方法及其应用", 中国管理科学, vol. 19, no. 6, pages 141 - 148 * |
| 李娜娜等: ""组合赋权法在电能质量综合评估中的应用", 电力系统保护与控制, vol. 37, no. 16, pages 128 - 134 * |
| 李娜娜等: "主客观权重相结合的电能质量综合评估", 电网技术, vol. 33, no. 6, pages 55 - 61 * |
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