CN104036431A - Interactive multilevel decision method of comprehensive evaluation in power quality based on cloud model - Google Patents
Interactive multilevel decision method of comprehensive evaluation in power quality based on cloud model Download PDFInfo
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- CN104036431A CN104036431A CN201410243956.4A CN201410243956A CN104036431A CN 104036431 A CN104036431 A CN 104036431A CN 201410243956 A CN201410243956 A CN 201410243956A CN 104036431 A CN104036431 A CN 104036431A
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Abstract
The invention discloses an interactive multilevel decision method of a comprehensive evaluation in power quality based on a cloud model. By using the cloud model, fuzziness and randomness are integrated together to constitute a mapping between qualitative and quantitative factors, and as a basis of information expression, the feature tallies with fuzziness and randomness of power quality grades. Subjectivity and objectivity can be well unified by an improved interactive multilevel decision model. Through combination of subjectivity and objectivity, a new comprehensive evaluation method of power quality based on the cloud model and the interactive decision is formed to achieve a more accurate, more objective and more scientific evaluation conclusion.
Description
Technical field
The present invention relates to the comprehensive assessment of power quality problem, relate in particular to the multi-level Interactive Decision Method of electric energy quality synthesis evaluation based on cloud model.
Background technology
Along with the progressively development of electric system, the quality of power supply is increasingly great on power supply and electricity consumption both sides impact.Use electric energy quality synthesis evaluation to evaluate the quality of electric energy, lay the foundation for improving the quality of power supply.There has been long research history in this field, has also obtained a lot of achievements in research.
Existing electric energy quality synthesis evaluation research method roughly can be divided into based on fuzzy mathematics, based on probability theory, three class methods based on intelligent algorithm.Wherein, based on the appraisal procedure of fuzzy mathematics, ambiguity feature that can fine embodiment power quality index, but in the time building degree of membership problem, fails fully to eliminate subjective factor, has affected to a certain extent the objectivity of method.Based on the energy quality comprehensive assessment method of probability theory, although probability statistics are combined with fuzzy mathematics, overcome to a certain extent the subjectivity problem of membership function, but the variation that its accuracy has very large probability to choose with index reference value changes.And appraisal procedure based on intelligent algorithm, though modeling is simple, needs very large assessment sample size conventionally, computing has very large triviality.
Summary of the invention
The object of this invention is to provide the multi-level Interactive Decision Method of electric energy quality synthesis evaluation based on cloud model, computing is simple, and accuracy is high.
The present invention adopts following technical proposals:
The multi-level Interactive Decision Method of electric energy quality synthesis evaluation based on cloud model, comprises following step:
Step 1, establishes comprehensive assessment index standard cloud model: based on cloud model characteristic, according to the ambiguity of electric energy quality synthesis evaluation qualitative index and randomness characteristic, qualitative index is transformed between quantification area and expressed, form the normal cloud model of index grade;
Step 2, determines each evaluation index weight: adopt multi-level Interactive Decision Method, objective weight number and actual conditions are iterated, until meet iteration precision requirement, iteration finishes, and finally determines the weighted value of the each index of electric energy quality synthesis evaluation;
Step 3, calculates the degree of association between each point to be assessed and standard normal cloud: build the correlation function between to be assessed water dust numerical value and standard normal cloud, calculate the degree of association between the two;
Step 4, determines quality of power supply grade: utilize calculated with weighted average method evaluation result, determine quality of power supply grade by evaluation result.
In described step 3, obtain the numerical characteristic (Ex, En, He) of cloud by calculation of relationship degree; Ex represents the distribution center of cloud, then produces a normal random number
, normal random number
obedience expectation value is
, standard deviation is
distribution; Finally make determinacy numerical value
for water dust, calculate water dust by following formula
belong to the degree of association y of this cloud:
.
In described step 4, determine that by evaluation result quality of power supply grade specifically comprises the following steps:
Steps A: according to the degree of association between the each index component of the sample to be assessed of trying to achieve and each evaluation grade standard normal cloud, obtain comprehensive evaluation matrix
;
Step B: in conjunction with comprehensive evaluation matrix
and weight coefficient
, draw comprehensive evaluation result vector
;
Step C: utilize method of weighted mean to draw evaluation result
, r can represent quality of power supply grade.
The present invention, by using cloud model, can be integrated together ambiguity and randomness, forms the mapping between qualitative and quantitative, and as the basis of information representation, the ambiguity of the inter-stages such as this characteristic and the quality of power supply and randomness are coincide.And improved multi-level Interactive Decision-Making model can be by unified well to subjectivity and objectivity.Both are combined, form the new energy quality comprehensive assessment method based on cloud model and Interactive Decision-Making, obtain more accurately more objective more scientific assessment result.
Brief description of the drawings
Fig. 1 is the process flow diagram of multi-layer Interactive Decision-Making model of the present invention;
Fig. 2 is process flow diagram of the present invention.
Embodiment
As shown in Figure 2, the multi-level Interactive Decision Method of electric energy quality synthesis evaluation based on cloud model, specifically comprise following step: step 1, establish comprehensive assessment index standard cloud model, based on cloud model characteristic, according to the ambiguity of electric energy quality synthesis evaluation qualitative index and randomness characteristic, qualitative index is transformed between quantification area and expressed, form the normal cloud model of index grade;
Normal cloud model can be expressed as (Ex, En, He).Wherein: Ex represents the distribution center of cloud, be the point value that can represent the corresponding grade boundary of quality of power supply concept; En is the measurement to attributive concept uncertainty degree, describes on the one hand the randomness of collecting sample data in electricity quality evaluation process, has portrayed on the other hand the ambiguity of the sample data scope that can be accepted by quality of power supply grade boundary concept; He is the entropy of En, and the dispersion degree of reflection quality of power supply sample data, has disclosed the relevance between randomness and the ambiguity of each factor in electricity quality evaluation.
In view of power quality index grade is interval number, can adopt index method of approximation to be translated into cloud data, regard the index [Cmin, Cmax] of two constraints by each index grade interval numerical value as, represent Ex with interval midrange, draw En according to " 3En " rule of Normal Cloud.That is:
(1)
(2)
Step 2, determines each evaluation index weight, adopts multi-level Interactive Decision Method, and objective weight number and actual conditions are iterated and determine the weight of the each index of electric energy quality synthesis evaluation.
Weight, also claims flexible strategy or weighting coefficient, embodies the relative significance level of indices.The present invention adopts improved multi-level Interactive Decision-Making model to determine index weights, can realize the two-way interaction of supplier of electricity and terminal electricity consumer.Multi-level Interactive Decision Method, subordinate adopts subjective enabling legislation to determine weight, and higher level's Raw performance weight is determined with VC Method, takes into account subjective power and the Objective Weight composed, and can increase the definite science of weight.As shown in Figure 1, that is: first determine weight constraints scope by higher level's supplier of electricity, in restriction range, determine initial reference weight vectors with VC Method, on this basis, in constraint, determine weight separately according to the preference of oneself by electricity consumption side of each subordinate, report supplier of electricity, supplier of electricity obtains considering again definite system weight after weight, feed back to again each user, constantly like this report and feed back, until stop after meeting certain accuracy requirement, finally determined the comprehensive weight of system by supplier of electricity.
Suppose the quality of power supply of n evaluation point to carry out comprehensive assessment, mainly consider wherein m evaluation index.For the quality of power supply of i point to be assessed (i=1,2 ..., j item evaluation index n) (j=1,2 ... m)
, can pass through every numerical value of following optimization problem
corresponding weight
objective function is:
（3）
Constraint condition:
（4）
Wherein
（5）
Construct a group system weights omega *=(ω 1*, ω 2* ...., ω m*) T, make it and n the weight vectors cosine of an angle sum maximum of trying to achieve.
（6）
Higher level determines after system reference weight, and this weight is fed back to subordinate, and subordinate can be to adjusting according to the definite weight of own preference for the first time again.For i unit, i=1,2 ..., n, can pass through following optimization problem
.Objective function is
（7）
Constraint condition is similar to formula (4).
So constantly, in the feedback adjusting of asking of upper and lower level, note higher level the m time and (m-1) the system reference weight of inferior iteration adjustment are W (m) * and W (m-1) *, if satisfy condition
（8）
When L is less than or equal to infinitesimal
time, stop the superior and the subordinate's feedback.Like this, through iterative, finally obtain the system weight W* of comprehensive assessment.
Step 3, calculates the degree of association between each point to be assessed and standard normal cloud: build the correlation function y between numerical value and standard normal cloud, compute associations degree.
Obtain the numerical characteristic (Ex, En, He) of cloud by calculation of relationship degree; Then produce a normal random number
, normal random number
obedience expectation value is
, standard deviation is
distribution; Finally make determinacy numerical value
for water dust, calculate water dust
belong to the degree of association y of this cloud:
（9）
Step 4: utilize calculated with weighted average method evaluation result, determine quality of power supply grade, specific as follows:
According to the degree of association between the each index component of the sample to be assessed of trying to achieve and each evaluation grade standard normal cloud, obtain comprehensive evaluation matrix
, in conjunction with weight coefficient
, draw comprehensive evaluation result vector
, utilize method of weighted mean to draw evaluation result
, r can represent quality of power supply grade.
（10）
Wherein:
for vector
respective components,
represent grade
score value, get respectively mark 1,2,3,4,5,6 by evaluation rank 1-6 herein.Described evaluation rank is determined according to regulation classification under IEEE.N is evaluation point number.
From formula, calculation in quantity index
and the degree of association between Normal Cloud
process there is enchancement factor, after computing repeatedly, can obtain the expectation value of final assessment result
and entropy
.
（11）
（12）
Wherein,
for operation times.After obtaining the expression numerical value of r, can determine the quality of power supply grade of evaluation point.
Claims (3)
1. the multi-level Interactive Decision Method of the electric energy quality synthesis evaluation based on cloud model, is characterized in that: comprise following step:
Step 1, establishes comprehensive assessment index standard cloud model: based on cloud model characteristic, according to the ambiguity of electric energy quality synthesis evaluation qualitative index and randomness characteristic, qualitative index is transformed between quantification area and expressed, form the normal cloud model of index grade;
Step 2, determines each evaluation index weight: adopt multi-level Interactive Decision Method, objective weight number and actual conditions are iterated, until meet iteration precision requirement, iteration finishes, and finally determines the weighted value of the each index of electric energy quality synthesis evaluation;
Step 3, calculates the degree of association between each point to be assessed and standard normal cloud: build the correlation function between to be assessed water dust numerical value and standard normal cloud, calculate the degree of association between the two;
Step 4, determines quality of power supply grade: the degree of association value that the weighted value obtaining by step 2 and step 3 obtain is utilized calculated with weighted average method evaluation result, determines quality of power supply grade by evaluation result.
2. the multi-level Interactive Decision Method of the electric energy quality synthesis evaluation based on cloud model according to claim 1, is characterized in that: the numerical characteristic (Ex, En, He) that obtains cloud in described step 3 by calculation of relationship degree; Ex represents the distribution center of cloud, then produces a normal random number
, normal random number
obedience expectation value is
, standard deviation is
distribution; Finally make determinacy numerical value
for water dust, calculate water dust by following formula
belong to the degree of association y of this cloud:
.
3. the multi-level Interactive Decision Method of the electric energy quality synthesis evaluation based on cloud model according to claim 2, is characterized in that: in described step 4, determine that by evaluation result quality of power supply grade specifically comprises the following steps:
Steps A: according to the degree of association between the each index component of the sample to be assessed of trying to achieve and each evaluation grade standard normal cloud, obtain comprehensive evaluation matrix
;
Step B: in conjunction with comprehensive evaluation matrix
and weight coefficient
, draw comprehensive evaluation result vector
;
Step C: utilize method of weighted mean to draw evaluation result
, r can represent quality of power supply grade.
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Cited By (6)
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| CN105512962A (en) * | 2016-01-13 | 2016-04-20 | 武汉大学 | Method for comprehensively evaluating insulation status of gas insulated switchgear (GIS) |
| CN106709192A (en) * | 2016-12-29 | 2017-05-24 | 国网内蒙古东部电力有限公司 | Power distribution network three-dimensional simulation training credibility evaluation method based on cloud matter-element model |
| CN107203842A (en) * | 2017-05-18 | 2017-09-26 | 西南交通大学 | Harmonic pollution level evaluation method based on extension cloud similarity and similarity to ideal solution |
| CN107679719A (en) * | 2017-09-20 | 2018-02-09 | 昆明理工大学 | A kind of complex electric network quality of power supply knowledge cloud monitoring and evaluation system and method |
| CN111583061A (en) * | 2020-04-30 | 2020-08-25 | 新智数字科技有限公司 | Power quality determination method and device, readable medium and electronic equipment |
| CN112668822A (en) * | 2020-09-14 | 2021-04-16 | 徐辉 | Scientific and technological achievement transformation platform sharing system, method, storage medium and mobile phone APP |
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Cited By (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN105512962A (en) * | 2016-01-13 | 2016-04-20 | 武汉大学 | Method for comprehensively evaluating insulation status of gas insulated switchgear (GIS) |
| CN105512962B (en) * | 2016-01-13 | 2018-07-06 | 武汉大学 | A kind of gas insulated combined electrical equipment state of insulation comprehensive estimation method |
| CN106709192A (en) * | 2016-12-29 | 2017-05-24 | 国网内蒙古东部电力有限公司 | Power distribution network three-dimensional simulation training credibility evaluation method based on cloud matter-element model |
| CN107203842A (en) * | 2017-05-18 | 2017-09-26 | 西南交通大学 | Harmonic pollution level evaluation method based on extension cloud similarity and similarity to ideal solution |
| CN107203842B (en) * | 2017-05-18 | 2020-07-17 | 西南交通大学 | Harmonic pollution level evaluation method based on extended cloud similarity and approximate ideal solution |
| CN107679719A (en) * | 2017-09-20 | 2018-02-09 | 昆明理工大学 | A kind of complex electric network quality of power supply knowledge cloud monitoring and evaluation system and method |
| CN111583061A (en) * | 2020-04-30 | 2020-08-25 | 新智数字科技有限公司 | Power quality determination method and device, readable medium and electronic equipment |
| CN112668822A (en) * | 2020-09-14 | 2021-04-16 | 徐辉 | Scientific and technological achievement transformation platform sharing system, method, storage medium and mobile phone APP |
| CN112668822B (en) * | 2020-09-14 | 2021-10-26 | 徐辉 | Scientific and technological achievement transformation platform sharing system, method, storage medium and mobile phone APP |
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