CN107305653A - Low-voltage power distribution station area integrated evaluating method and device based on attribute mathematicses - Google Patents
Low-voltage power distribution station area integrated evaluating method and device based on attribute mathematicses Download PDFInfo
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Abstract
The present invention relates to a kind of low-voltage power distribution station area integrated evaluating method based on attribute mathematicses, the low-voltage power distribution station area integrated evaluating method includes：Obtain whole evaluation indexes of low-voltage power distribution station area；Obtain the subjective weight and objective weight of whole evaluation indexes；The actual weight of each evaluation index is obtained according to subjective weight and objective weight；Overall merit is carried out to the low-voltage power distribution station area using whole evaluation index combination attribute mathematicses.The device that the present invention is provided is used to realize the above method.The present invention can evaluation result that is more comprehensive and accurately drawing separate unit area or Duo Tai areas.
Description
Technical field
The present invention relates to intelligent power distribution network technology field, more particularly to a kind of low-voltage power distribution station area based on attribute mathematicses are comprehensive
Close evaluation method and device.
Background technology
Intelligent distribution network region be directly facing user as a part for intelligent grid, be also to ensure power supply quality, improve power network
Operational efficiency, the key link of Innovative User service.In the government work report of 2016, " strengthen supply side structural reform,
Strengthen sustainable growth power " turn into the Main way of State Grid Corporation of China's this year reform.For the demand side pipe of low-voltage network
Reason and reform, demand and experience based on power consumer, which then turn into, evaluates one of its main standard reformed, and State Council issues
" electricity changes No. 9 texts " propose move forward steadily sale of electricity side reform, in order to social capital decontrol the placing electric industry business.Different electric power is public
Department is added to the placing electric industry business so that intensified competition.But it is due to that the standard evaluation do not evaluated intelligent distribution network refers to
Mark system, easily causes between the intelligent distribution network that different electric companies are built and there is incompatible phenomenon.
The different demands of power consumer determine that its evaluation experienced to electricity consumption has obvious subjective differences.Such as Fig. 1 institutes
Show, power consumer now is not only the user of electric power, can also be the participant at generating end, they can also be used as hair
Electric enterprise is participated in the operation of low-voltage network.So, power consumer of today is not concerned only with the reliability of electricity consumption, economy
Type, more focusing on the quality and use of electricity consumption can service.This just promotes electric company, it has to consider power consumer to electric energy
Different demands, change its management philosophy from " managing customer " to " services client ", and require that Utilities Electric Co. can take to power supply
Business quality is evaluated, and the weak link of electric service is found in time, targetedly problem is improved, constantly lifting electricity
The service ability of power company.
Many scholars do a lot of work in terms of intelligent distribution network evaluation.For example in conventional integrated evaluating method,
Fuzzy comprehensive evaluation method and neural network have more application, but they have respective limitation：In fuzzy synthesis
In the application of judge method, the construction of membership function has random (being unsatisfactory for additive property) in fuzzy mathematics, takes and takes small fortune greatly
The information of large quantities of medians is easily lost in calculation, therefore the classification irrational problem of unclear, result occurs；And maximum membership degree
Principle is not often suitable for the identification of orderly evaluate collection again.For neural network model, due to needing artificially design grid
Network parameter, needs many experiments to attempt just to can determine that Internet number and each layer neuron number in the design process；In addition, study
Parameter is also required to debug repeatedly, or even the factor of influence learning parameter also needs to re -training when changing.
The content of the invention
For defect of the prior art, the present invention provides a kind of low-voltage power distribution station area overall merit based on attribute mathematicses
Method and device, more can draw comprehensively and accurately the evaluation result in separate unit area or Duo Tai areas, be gathered around without power consumer
There is professional knowledge to realize, it is more humane.
In a first aspect, the invention provides a kind of low-voltage power distribution station area integrated evaluating method based on attribute mathematicses, it is described
Low-voltage power distribution station area integrated evaluating method includes：
Obtain whole evaluation indexes of low-voltage power distribution station area；
Obtain the subjective weight and objective weight of whole evaluation indexes；
The actual weight of each evaluation index is obtained according to subjective weight and objective weight；
Overall merit is carried out to the low-voltage power distribution station area using whole evaluation index combination attribute mathematicses.
Alternatively, G1 expert is passed through in the step of subjective weight and objective weight of acquisition whole evaluation indexes
Enabling legislation obtains subjective weight；And/or objective weight is obtained by entropy assessment.
Alternatively, G1 expert's assignment method comprises the following steps：
Whole evaluation indexes are given a mark by multidigit expert；Classification according to each evaluation index is ranked up；
Calculate the size of weight ratio between adjacent evaluation index；
According to weight of the weight sum for the 1 each evaluation index of principle acquisition；
Marking according to the multidigit expert to each evaluation index, calculates the average value of each evaluation criterion weight, with
Obtain the subjective weight of the evaluation index.
Alternatively, the entropy assessment comprises the following steps：
Evaluations matrix is determined according to the data of whole evaluation indexes；
The Evaluations matrix is handled to obtain normalized matrix；
Obtain the entropy and coefficient of variation of each evaluation index；
The entropy weight i.e. objective weight of each evaluation index of each evaluation index is obtained according to the entropy and coefficient of variation.
Alternatively, it is described each evaluation index is obtained according to subjective weight and objective weight actual weight the step of also wrap
Include：
Obtain the subjective weight of each evaluation index and the distance of objective weight to obtain subjective weight using distance function
With the distribution coefficient of objective weight；
The actual power of each evaluation index is obtained according to subjective weight and its distribution coefficient, objective weight and its distribution coefficient
Weight.
Alternatively, it is described that the low-voltage power distribution station area is integrated using whole evaluation index combination attribute mathematicses
The step of evaluation, includes：
Determine the PASCAL evaluation PASCAL grade of Needs index to obtain ordered partition class according to user's request；
Criteria for classification matrix is determined according to the good and bad degree of the ordered partition class and each evaluation index；
Interval composition attributive measure function matrix is estimated according to single item evaluation Criterion Attribute；
The synthesized attribute for obtaining each evaluation index by ranking operation estimates interval；
Confidence level is set to obtain the grade that evaluation index belongs in ordered partition class.
Second aspect, the embodiment of the present invention additionally provides a kind of low-voltage power distribution station area overall merit dress based on attribute mathematicses
Put, the low-voltage power distribution station area overall merit device includes：
Evaluation index acquisition module, whole evaluation indexes for obtaining low-voltage power distribution station area；
Subjective and objective Weight Acquisition module, subjective weight and objective weight for obtaining whole evaluation indexes；
Actual weight acquisition module, the actual power for obtaining each evaluation index according to subjective weight and objective weight
Weight；
Overall merit module, for being entered using whole evaluation index combination attribute mathematicses to the low-voltage power distribution station area
Row overall merit.
Alternatively, the subjective and objective Weight Acquisition module obtains subjective weight by G1 expert's enabling legislation and included：
Whole evaluation indexes are given a mark by multidigit expert；Classification according to each evaluation index is ranked up；
Calculate the size of weight ratio between adjacent evaluation index；
According to weight of the weight sum for the 1 each evaluation index of principle acquisition；
Marking according to the multidigit expert to each evaluation index, calculates the average value of each evaluation criterion weight, with
Obtain the subjective weight of the evaluation index；
And/or included by entropy assessment acquisition objective weight：
Evaluations matrix is determined according to the data of whole evaluation indexes；
The Evaluations matrix is handled to obtain normalized matrix；
Obtain the entropy and coefficient of variation of each evaluation index；
The entropy weight i.e. objective weight of each evaluation index of each evaluation index is obtained according to the entropy and coefficient of variation.
Alternatively, the actual weight acquisition module obtains actual weight by following steps and included：
Obtain the subjective weight of each evaluation index and the distance of objective weight to obtain subjective weight using distance function
With the distribution coefficient of objective weight；
The actual power of each evaluation index is obtained according to subjective weight and its distribution coefficient, objective weight and its distribution coefficient
Weight.
Alternatively, the overall merit module obtains each grade for commenting index by following steps and included：
Determine the PASCAL evaluation PASCAL grade of Needs index to obtain ordered partition class according to user's request；
Criteria for classification matrix is determined according to the good and bad degree of the ordered partition class and each evaluation index；
Interval composition attributive measure function matrix is estimated according to single item evaluation Criterion Attribute；
The synthesized attribute for obtaining each evaluation index by ranking operation estimates interval；
Confidence level is set to obtain the grade that evaluation index belongs in ordered partition class.
As shown from the above technical solution, the present invention according to the connotation of intelligent low-pressure power distribution network, feature and country to demand
Side management and the situation of attention further of reform, based on this present situation, by analyzing, combing existing low-voltage network index of correlation,
Construct the low-voltage power distribution station area assessment indicator system based on user's request.Take into account the experience preference of expert and the objective letter of index
Breath, and intensity of variation according to subjective and objective distance function and the relation of distribution coefficient fluctuation take the principle waited, acquisition actual weight.
The fluctuation of real system service data is considered simultaneously, and traditional data dot values are replaced with the interval value of achievement data, can be more
Real reaction low-voltage network actual motion feature.The present invention more can draw comprehensively and accurately separate unit area or many
The evaluation result in area.
Brief description of the drawings
The features and advantages of the present invention can be more clearly understood from by reference to accompanying drawing, accompanying drawing is schematical without that should manage
Solve to carry out any limitation to the present invention, in the accompanying drawings：
Fig. 1 is the relation schematic diagram of power consumer and grid company；
Fig. 2 is a kind of stream of low-voltage power distribution station area integrated evaluating method based on attribute mathematicses provided in an embodiment of the present invention
Journey schematic diagram；
Fig. 3 is low-voltage power distribution station area assessment indicator system schematic diagram provided in an embodiment of the present invention；
Fig. 4 is that low-voltage power distribution station area electricity consumption constitutes situation schematic diagram；
Fig. 5 is a kind of frame of low-voltage power distribution station area overall merit device based on attribute mathematicses provided in an embodiment of the present invention
Figure.
Embodiment
To make the purpose, technical scheme and advantage of the embodiment of the present invention clearer, below in conjunction with the embodiment of the present invention
In accompanying drawing, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described embodiment is
A part of embodiment of the present invention, rather than whole embodiments.Based on the embodiment in the present invention, those of ordinary skill in the art
The every other embodiment obtained under the premise of creative work is not made, belongs to the scope of protection of the invention.
In practical application, in the research process to low-voltage power distribution station area integrated evaluating method, inventor has found：Electric power is used
Family be not as expert equally be familiar with mostly technical evaluation index appraisement system, add its knowledge, the limitation of experience with
And the difference of respective demand, power consumer is difficult to have a quantitative judgement to opinion rating, is even difficult to provide corresponding sometimes
Evaluation information.Power consumer is desirable for meeting thinking in images and the mode of integrality description is commented power distribution station
Valency.Therefore it is to meet power consumer to have low-voltage power distribution station area progress general survey that inventor, which is thought using Linguistic Assessment Information,
Efficacious prescriptions method.
Based on this, the invention provides a kind of low-voltage power distribution station area integrated evaluating method based on attribute mathematicses, such as Fig. 2 institutes
Show, the low-voltage power distribution station area integrated evaluating method includes：
S1, the whole evaluation indexes for obtaining low-voltage power distribution station area；
S2, the subjective weight and objective weight for obtaining whole evaluation indexes；
S3, the actual weight for obtaining according to subjective weight and objective weight each evaluation index；
S4, using whole evaluation index combination attribute mathematics theories the low-voltage power distribution station area is carried out integrating and commenting
Valency.
The present invention according to the different needs for electricity of power consumer by determining whole evaluation indexes and each evaluation index
Subjective weight, objective weight and actual weight, it is contemplated that each power consumer custom and low-voltage power distribution station area service data
Fluctuation, using evaluation index come instead of traditional service data；It is right by whole evaluation index combination attribute data theories
Low-voltage power distribution station area carries out overall merit.The evaluation result of the present invention is simply clear and definite, facilitates power consumer to use.
To embody the superiority for the low-voltage power distribution station area integrated evaluating method based on attribute mathematicses that the present invention is provided, below
Each step is described further with accompanying drawing in conjunction with the embodiments.
First, the step of introducing S1, obtain whole evaluation indexes of low-voltage power distribution station area.
Low-voltage power use is constructed in the embodiment of the present invention in terms of reliability, quality, economy and use can service four
The assessment indicator system of family power distribution station.
It should be noted that in order to which later stage evaluation needs, each evaluation index is divided into profit evaluation model in the embodiment of the present invention
Evaluation index, osculant evaluation index and cost type evaluation index, the definition that wherein evaluation index is the bigger the better are commented for profit evaluation model
Valency index, optimal value is osculant evaluation index in the definition of some middle numerical value, and the smaller the better definition of evaluation index is into
This type evaluation index.
First, as shown in figure 3, including power supply reliability RS-1, power supply reliability RS-2, power supply for reliability evaluation index
Reliability RS-3, average power off time of user, average frequency of power cut of user and user's mean down time etc..
1) power supply reliability includes power supply reliability RS-1, power supply reliability RS-2, power supply reliability RS-3, three evaluations
Index is profit evaluation model evaluation index.Wherein power supply reliability RS-1 statistics is non-power off time accounting, power supply reliability RS-
2 statistics are the non-power off time accountings for removing external action, and power supply reliability RS-3 statistics is to remove the non-power failure rationed the power supply
Time accounting.External action refers to the power network and facility of non-enterprise operation, maintenance and management, and its fault outage belongs to external action
Have：External force destruction, natural calamity, urban construction etc..
Characterize power supply reliability three evaluation index calculation formula be respectively：
2) average power off time of user is：
3) average frequency of power cut of user is：
4) user's mean failure rate power off time is：
It should be noted that above-mentioned average power off time of user, average frequency of power cut of user and user's mean failure rate stop
The electric time, be all using it is small be it is excellent i.e. they as cost type evaluation index.
2nd, power consumer includes the requirement to the quality of power supply, electric service to the demand of quality.As shown in figure 3, electric energy
The evaluation index of quality includes：Rate of qualified voltage, frequency qualification rate, flickering qualification rate, voltage unbalance factor qualification rate and voltage
Total harmonic distortion factor etc.；For electric service requirement evaluation index include intelligent electric meter coverage rate, ammeter information acquisition rate and
95598 portal website's coverage rates.
(1) rate of qualified voltage, it is each to obtain power consumer rate of qualified voltage in the rate of qualified voltage of each monitoring point, grid
The average value of monitoring point rate of qualified voltage, calculation formula is：
(2) cross conference due to frequency departure to impact asynchronous motor and electronic equipment, be that this present invention is implemented
Using frequency qualification rate as an evaluation index in example, calculation formula is：
(3) voltage flicker can be damaged to power load.For example cause illuminating lamp to flash, cause motor speed unstable
It is fixed etc..Flickering qualification rate calculation formula is：
(4) Voltage unbalance can cause induction conductivity, computer can not normal work.The evaluation index of the invention is into
This type evaluation index, national regulations power system points of common connection voltage unbalance factor permissible value is 2%, is connected to points of common connection
Each user cause the voltage not permissibility be 1.3%.The voltage unbalance factor taken in the present invention is in platform area unit
The average value for the voltage tri-phase unbalance factor that all measuring point measuring instruments are surveyed, its calculation formula is as follows：
(5) for user, harmonic wave is too high the problems such as can cause electric energy metrical mistake, shorten motor service life, can also
Communication system is influenceed, electromagnetic interference is produced, makes telecommunications Quality Down.This evaluation index is cost class evaluation index, national regulations
The total harmonic distortion factor limit value of 380V voltages is that 5%, 10kV voltage total harmonic distortion factors limit value is 4%.Institute's power taking in the present invention
Press the voltage total harmonic distortion that total harmonic distortion factor is points of common connection in power distribution station.
3rd, in terms of power consumer is mainly electricity price to the demand of economy, at present by taking Beijing area as an example, resident living is used
The tentative step price of electricity, and peak and valley time sales rate of electricity policy is carried out to non-resident electricity consumption, in addition, connecing with distributed power source
Enter, can also produce influence to electricity consumption economy.Electricity consumption composition situation for a low-voltage power distribution station area substantially can be by Fig. 4 tables
Show.
According to the electricity consumption situation of power consumer, in the embodiment of the present invention using accounted for spontaneous electricity in year year total electricity consumption it
Account for the ratio between year total civil power power consumption than, spike year, power consumption period and year generation of electricity by new energy amount to account for the ratio between year gross generation etc. several
Evaluation index.
(1) accounting for the ratio between year total electricity consumption with spontaneous electricity in year is：
(2) year spike period power consumption accounts for the ratio between year total civil power power consumption and is：
It should be noted that the spike period is the load maximum period for power network, electricity price highest is not influenceing life
Produce in the case of living, period institute's power consumption should be reduced as far as possible, this evaluation index is cost type evaluation index.
(3) year electricity volume accounts for the ratio that new energy annual electricity generating capacity in the ratio between year gross generation Zhi Tai areas accounts for year gross generation,
Its calculation formula is：
This evaluation index is higher to represent that user is higher to Self-energy-generating utilization rate, is profit evaluation model evaluation index.
4th, use can service including intelligent electric meter coverage rate, carry out dynamic electricity price user power utilization amount ratio, 95588 power supply clothes
Business system coverage rate and self-service power supply service terminal system coverage rate etc..
(1) intelligent electric meter coverage rate.Intelligent electric meter can ensure that user checks power information etc. at any time.The evaluation index reflects
Intelligent electric meter accounts for the installation situation of total electric supply meter, and this evaluation index is profit evaluation model evaluation index.Calculation formula is as follows：
(2) dynamic electricity price user power utilization amount ratio is carried out.Rational dynamic electricity price mechanism can encourage user's using electricity wisely,
Efficiency is improved, load factor is improved.The annual user power utilization amount ratio for carrying out dynamic electricity price is used in the present invention as evaluation
The evaluation index of dynamic electricity, relative to using carry out dynamic electricity price number of users ratio it is more objective, accurate, can reflect due to
The influence that Demand Side Response caused by dynamic electricity price is produced to distribution network operation.This evaluation index is profit evaluation model evaluation index.Its
Calculation formula is：
(3) 95598 portal website's coverage rates.The power information of each user can be inquired about in 95598 portal websites, is defined
95598 portal website's coverage rate evaluation indexes can realize the situation with user interaction to reflect by website.In this evaluation index
The number of users of system covering refer in system can Query Information number of users, the calculation formula of its coverage rate is：
(4) 95598 electric service system coverage rates.95598 electric service systems provide the user spirit by voice service
Various interaction function living, 95598 electric service system coverage rates should come reflect the voice service system defined in the present invention
With degree, its calculation formula is as follows：
(5) self-service power supply service terminal system coverage rate.Self-service power supply service terminal system, can be business hall customer self-service
Power purchase (paying dues), supplement with money and customer electricity information inquiry provide facility, so as to improve operating efficiency, improve service quality and client
Satisfaction.The calculation formula for defining its coverage rate is：
For user, 95598 portal websites, 95595 electric service systems and self-service power supply service terminal system, all
It is that can improve the quality to user service, the evaluation index is profit evaluation model evaluation index.
It should be noted that describe above-mentioned every evaluation index in the embodiment of the present invention, those skilled in the art can be with
Understand, power consumer can select different evaluation indexes as the case may be, be equally applicable in this method, the present invention
It is not construed as limiting.
Secondly, the step of introducing S2, obtain the subjective weight and objective weight of whole evaluation indexes.
First, the subjective weight of whole evaluation indexes is obtained
For take into account in the need for electricity and subjective desire of power consumer, the embodiment of the present invention using subjectivity marking in the form of come
Reflect the opinion of power customer, intuitive is strong and calculation is relatively easy, and the leeway of selection is larger.Preferably, the present invention is real
Apply the subjective weight for selecting G1 methods to determine evaluation index in example.G1 methods are a kind of according to first to evaluation index in the embodiment of the present invention
Qualitative sequence is carried out, then importance ratio in judgement is carried out to adjacent evaluation index, the subjective weights of quantitative calculating are finally carried out again
Method.The advantage of G1 methods is without development of judgment matrix, without consistency check is carried out, with construction AHP (analytic hierarchy process (AHP))
Judgment matrix is reduced at double compared to amount of calculation, and scheme number is not limited in the application.Determine to evaluate using G1 methods
Index weights, it is workable, it is easy to application.
For example, power consumer is by inviting the several experts and scholars of Utilities Electric Co., power supply administration and government department to participate in marking,
The importance degree of evaluation index is judged according to expert estimation, importance ranking is provided；Then integrate multidigit expert's
Experience opinion, appropriate assignment is given to the ratio of evaluation index importance degree, finally by weighted calculation, show that an energy is simultaneous
The weight of Gu Duowei expert's wish.
1) so that certain expert estimation obtains weight as an example, its concrete operation step is as follows：
(1) certain expert gives a mark to evaluation index
Certain expert gives a mark to evaluation index, gives a mark as numerical value between 1~10, evaluation index it is more important marking value should be more
It is high.Table design of giving a mark is as shown in table 1.
The expert estimation table of table 1
| Evaluation index | x1 | x2 | … | xm |
| Score value |
(2) determine that evaluation index significance level sorts
Evaluation index is designated as x1, x2..., xm, graded according to expert, evaluation index carried out according to significance level
Sequence, if evaluation index xiImportance degree be more than (or not less than) evaluation index xjThen it is designated as：xi＞ xj.If according to certain position
The importance sorting of expert estimation evaluation index is：
x1＞ x2＞ ... ＞ xm (19)
(3) Calculation Estimation index weights
The evaluation index marking situation provided first according to expert, calculates the ratio of weight size between adjacent evaluation index
Value, evaluation index wk-1With wkThe ratio between weight is designated as：
Further according to adjacent evaluation criterion weight ratio, and the principle that each weight sum is 1, calculate each evaluation index wm
Weight：
The weight of other evaluation indexes can be tried to achieve by stepping type：
wk-1=rkwk, k=m, m-1, m-2 ..., 3,2 (22)
2) multidigit expert estimation determines final weight
If having j experts and scholars to give a mark to evaluation index, then weight obtained by evaluation index m is designated as ωm1~
wmj, in order to objectively integrate expertise and subjective desire, average computation is weighted to it, evaluation index is obtained and finally weighs
Weight.
2nd, the objective weight of whole evaluation indexes is obtained
The objective weight of whole evaluation indexes is determined in the embodiment of the present invention using entropy assessment.I.e. entropy assessment is former based on entropy
The Weight Determination drawn is managed, the objective weighted model of how much judgement weights of information content is included according to each evaluation index.Comment
The entropy of valency index is smaller, and the information provided is more；Evaluation index is more important, and corresponding weight is also bigger.
When object to be evaluated has m, each object has n evaluation index, and the step of determining weight using entropy assessment is as follows：
(1) Evaluations matrix B=(b are determined according to initial dataij)m×n, i=1,2 ..., m；J=1,2 ..., n, wherein bij
For j-th of evaluation index value of i-th of evaluation object.Matrix form such as following formula：
(2) unification and standardization are carried out to Evaluations matrix, obtains normalized matrix S=(sij)m×n, eliminate and evaluate
Index incommensurability.Evaluation index standardized method is as follows：
(3) entropy of each evaluation index is：
Work as sijWhen=0, s is madeijlnsij=0.
(4) coefficient of variation for defining j-th of evaluation index is：
αj=1-Ej(j=1,2 ..., n) (26)
The entropy weight of (5) j-th of evaluation index is：
Entropy weight vjThe number of evaluation index information contained amount is embodied, while reflecting the significance level of evaluation index, i.e.,
The bigger effect for representing the evaluation index played in appraisement system of entropy weight of evaluation index is bigger.
Again, the step of introducing S3, the actual weight of each evaluation index obtained according to subjective weight and objective weight.
In practical application, subjective weighting method can have certain subjective preferences, it is difficult to break away from human factor, and Objective Weight
Method constitutes decision matrix according to evaluation index actual information, and weight is formed by objective computing.In order to take into account the warp of expert simultaneously
The objective information of preference and evaluation index is tested, the advantage that the present invention integrates subjective and Objective Weight using Evaluation formula determines each
The weight of evaluation index, wherein determining subjective weight using the G1 methods based on expert estimation, objective weighted model uses entropy assessment.
If the subjective weight that the G1 methods based on expert estimation are determined is U=(u1,u2,…,un), use the entropy of Objective Weight
The weight that power method is obtained is V=(v1,v2,…,vn), if both distance functions are D (U, V), expression formula is：
If subjective and objective comprehensive weight is W, expression formula is as follows：
W=α U+ β V, alpha+beta=1 (29)
α, β are respectively the distribution coefficient of subjective weight and objective weight in formula (29).
In order to consider the authenticity of subjective experience and preference and objective data information simultaneously, the present invention take make it is subjective and objective
The principle that the relation of intensity of variation and the distribution coefficient fluctuation of distance function takes etc., to ensure the difference degree between different weights
Difference degree between distribution coefficient is consistent, and finally realizes subjective and objective unification.Its expression formula is as follows：
D(U,V)2=(alpha-beta)2 (30)
With reference to formula (23) (27), you can obtain the weighted value of subjective and objective synthesis, be designated as：
W=(w1,w2,…,wm) (31)
Finally, introduce S4, the low-voltage power distribution station area is entered using whole evaluation index combination attribute mathematics theories
The step of row overall merit.
Attribute mathematicses assign attribute as set from the angle of thinking, it is proposed that property set, attribute space and attribute can survey sky
Between concept, attribute mathematicses can solve the problems, such as the comprehensive assessment with multiple evaluation indexes, multiple Fog properties well.It has
The evaluation of body realizes that step is as follows：
(1) interal separation based on user's request attribute evaluation
Assuming that F is certain generic attribute space on X, with reference to the evaluation object of the present invention, then { low-voltage power distribution station area runs shape to F=
State }, X={ Monitoring Data of each index day part }.
C1,C2,…,CKIt is K attribute Interval Set in attribute space F, whenAndThen
(C1,C2,…,CK) it is a segmentation class of attribute measure space, and meet C1<C2<…<CKOr C1>C2>…>CK, then, by belonging to
Property composition K grade Special composition assessment set (C1,C2,…,CK) be attribute measure space an ordered partition class,
Think that assessment result is more big more " strong " in the comprehensive assessment of the present invention：Take C1<C2<…<CK。
Because general power consumer is not as the appraisement system that expert is equally familiar with technical evaluation index mostly, add
The difference of its knowledge, the limitation of experience and respective demand, user is difficult to have a quantitative judgement to opinion rating, is had
When even be difficult to provide corresponding evaluation information.Therefore, the evaluation index of low-voltage power distribution station area is entered using Linguistic Assessment Information
It is the direct effective means for meeting general user that row, which is evaluated,.
User is divided into 5 basic grades to the PASCAL evaluation PASCAL of electrical energy demands evaluation index in the present invention：It is excellent, good, in, compared with
It is poor, poor.Then K=5, C1={ poor }, C2={ poor }, C3=in, C4={ good } and C5={ excellent }.
(2) determination of ordered partition class
With reference to the research object in the present invention, CkIt is the ordered partition class of low-voltage power distribution station area running status, is commented in synthesis
Think that assessment result is more big more " strong ", i.e. C in estimating1<C2<…<CK.According to the priority orders of power distribution station running status, this hair
The bright ordered partition class by low-voltage power distribution station zone state be ordered as it is poor, it is poor, in, it is good, excellent.Corresponding each state evaluation refers to
Mark ImCan also be according to CkSplit, form the criteria for classification matrix of the good and bad degree of m evaluation of running status index of description, such as
Shown in lower：
In criteria for classification matrix, the data area [a of j-th of evaluation index in certain periodjk,bjk] it is IjIn attribute interval F
On k-th of segmentation it is interval, meet ajk≤bjk, k=1,2 ..., K.
(3) single item evaluation Criterion Attribute estimates the determination in interval
It is I to each m evaluation index of operation sample measurement1、I2、…、ImIf being estimated by single item evaluation Criterion Attribute
The attributive measure function matrix that interval is constituted is [μi], then the attributive measure function matrix of m evaluation index is as follows：
In formula, [μ ik,] it is j-th of evaluation index I of evaluation objectjIn segmentation C in orderKAttribute Measure,μ ikFor lower bound
Attribute Measure,For upper bound Attribute Measure.If aj1<aj2<…<ajK, bj1<bj2<…<bjK, calculate xijIn segmentation C in orderKOn
Each attributive measure function：
It is hereby achieved that the single item evaluation Criterion Attribute of evaluation object estimates the attributive measure function matrix of interval composition.
(4) synthesized attribute estimates the determination in interval
The combining weights calculated according to step S3, and single item evaluation Criterion Attribute with reference to obtained by above formula estimates interval,
The synthesized attribute for obtaining evaluation object by ranking operation estimates interval.(33),
Obtain specific expression formula as follows：
Furthermore, processing of being averaged to the attributive measure function of each evaluation index is designated as
Then final synthesized attribute measure vector is：
(5) Reliability Code is recognized
Setting reliability is λ, and λ typically takes 0.6 or 0.7, and the present invention takes λ=0.65, is calculated as follows formula, works as C1<C2<…<CK
When,
Work as C1>C2>…>CKWhen,
Evaluated object can then be picked out and particularly belong to CkGrade.
In order to which the evaluation to single low-voltage power distribution station area can not only be realized, sometimes also need to obtain multiple low-voltage distributions
The grade ranking and fellow peers' evaluation situation in platform area.However, in a practical situation, in order to realize multiple area's industries to timestamp,
Application attribute is estimated to be picked out after graded category with Reliability Code, may there is the feelings that multiple objects belong to same grade
Condition, it is impossible to draw more objective and accurate evaluation result.Therefore, the present invention uses expert point rating method, if grade CkIt is corresponding
Fraction is sk, then evaluation object TiScore be designated as Pi：
By grade and score calculation, the evaluation knot in separate unit area or Duo Tai areas can more fully and be accurately drawn
Really.
In addition, the embodiment of the present invention additionally provides a kind of low-voltage power distribution station area overall merit device based on attribute mathematicses,
As shown in figure 5, the low-voltage power distribution station area overall merit device includes：
Evaluation index acquisition module M1, whole evaluation indexes for obtaining low-voltage power distribution station area；
Subjective and objective Weight Acquisition module M2, subjective weight and objective weight for obtaining whole evaluation indexes；
Actual weight acquisition module M3, the actual power for obtaining each evaluation index according to subjective weight and objective weight
Weight；
Overall merit module M4, for utilizing whole evaluation index combination attribute mathematicses to the low-voltage power distribution station area
Carry out overall merit.
Alternatively, the subjective and objective Weight Acquisition module M2 obtains subjective weight by G1 expert's enabling legislation and included：
Whole evaluation indexes are given a mark by multidigit expert；Classification according to each evaluation index is ranked up；
Calculate the size of weight ratio between adjacent evaluation index；
According to weight of the weight sum for the 1 each evaluation index of principle acquisition；
Marking according to the multidigit to each evaluation index, calculates the average value of each evaluation criterion weight, to obtain
The subjective weight of the evaluation index；
And/or included by entropy assessment acquisition objective weight：
Evaluations matrix is determined according to the data of whole evaluation indexes；
The Evaluations matrix is handled to obtain normalized matrix；
Obtain the entropy and coefficient of variation of each evaluation index；
The entropy weight i.e. objective weight of each evaluation index of each evaluation index is obtained according to the entropy and coefficient of variation.
Alternatively, the actual weight acquisition module M3 obtains actual weight by following steps and included：
Obtain the subjective weight of each evaluation index and the distance of objective weight to obtain subjective weight using distance function
With the distribution coefficient of objective weight；
The actual power of each evaluation index is obtained according to subjective weight and its distribution coefficient, objective weight and its distribution coefficient
Weight.
Alternatively, the overall merit module M4 obtains each grade for commenting index by following steps and included：
Determine the PASCAL evaluation PASCAL grade of Needs index to obtain ordered partition class according to user's request；
Criteria for classification matrix is determined according to the good and bad degree of the ordered partition class and each evaluation index；
Interval composition attributive measure function matrix is estimated according to single item evaluation Criterion Attribute；
The synthesized attribute for obtaining each evaluation index by ranking operation estimates interval；
Confidence level is set to obtain the grade that evaluation index belongs in ordered partition class.
Because low-voltage power distribution station area overall merit device provided in an embodiment of the present invention is based on low-voltage distribution provided above
Platform area integrated evaluating method is realized, thus can be solved identical technical problem as method, reaches that identical technology is imitated
Really, it will not be repeated here.
In the present invention, term " first ", " second ", " the 3rd " are only used for describing purpose, and it is not intended that indicate or
Imply relative importance.Term " multiple " refers to two or more, unless otherwise clear and definite restriction.
Although being described in conjunction with the accompanying embodiments of the present invention, those skilled in the art can not depart from this hair
Various modifications and variations are made in the case of bright spirit and scope, such modifications and variations are each fallen within by appended claims
Within limited range.
Claims (10)
1. a kind of low-voltage power distribution station area integrated evaluating method based on attribute mathematicses, it is characterised in that the low-voltage power distribution station area
Integrated evaluating method includes：
Obtain whole evaluation indexes of low-voltage power distribution station area；
Obtain the subjective weight and objective weight of each evaluation index；
The actual weight of each evaluation index is obtained according to subjective weight and objective weight；
Overall merit is carried out to the low-voltage power distribution station area using whole evaluation index combination attribute mathematicses.
2. low-voltage power distribution station area integrated evaluating method according to claim 1, it is characterised in that the acquisition whole is commented
Subjective weight is obtained by G1 expert's enabling legislation in the step of subjective weight and objective weight of valency index；And/or pass through entropy weight
Method obtains objective weight.
3. low-voltage power distribution station area integrated evaluating method according to claim 2, it is characterised in that G1 expert's assignment method bag
Include following steps：
Whole evaluation indexes are given a mark by multidigit；Classification according to each evaluation index is ranked up；
Calculate the size of weight ratio between adjacent evaluation index；
According to weight of the weight sum for the 1 each evaluation index of principle acquisition；
Marking according to the multidigit to each evaluation index, calculates the average value of each evaluation criterion weight, is commented with obtaining this
The subjective weight of valency index.
4. low-voltage power distribution station area integrated evaluating method according to claim 2, it is characterised in that the entropy assessment includes following
Step：
Evaluations matrix is determined according to the data of whole evaluation indexes；
The Evaluations matrix is handled to obtain normalized matrix；
Obtain the entropy and coefficient of variation of each evaluation index；
The entropy weight i.e. objective weight of each evaluation index of each evaluation index is obtained according to the entropy and coefficient of variation.
5. the low-voltage power distribution station area integrated evaluating method according to claim 3 or 4, it is characterised in that described according to subjectivity power
The step of weight and objective weight obtain the actual weight of each evaluation index also includes：
The subjective weight of each evaluation index and the distance of objective weight are obtained using distance function to obtain subjective weight and visitor
See the distribution coefficient of weight；
The actual weight of each evaluation index is obtained according to subjective weight and its distribution coefficient, objective weight and its distribution coefficient.
6. low-voltage power distribution station area integrated evaluating method according to claim 1, it is characterised in that described to be commented using the whole
The step of valency index combination attribute mathematicses carry out overall merit to the low-voltage power distribution station area includes：
Determine the PASCAL evaluation PASCAL grade of Needs index to obtain ordered partition class according to user's request；
Criteria for classification matrix is determined according to the good and bad degree of the ordered partition class and each evaluation index；
Interval composition attributive measure function matrix is estimated according to single item evaluation Criterion Attribute；
The synthesized attribute for obtaining each evaluation index by ranking operation estimates interval；
Confidence level is set to obtain the grade that evaluation index belongs in ordered partition class.
7. a kind of low-voltage power distribution station area overall merit device based on attribute mathematicses, it is characterised in that the low-voltage power distribution station area
Overall merit device includes：
Evaluation index acquisition module, whole evaluation indexes for obtaining low-voltage power distribution station area；
Subjective and objective Weight Acquisition module, subjective weight and objective weight for obtaining whole evaluation indexes；
Actual weight acquisition module, the actual weight for obtaining each evaluation index according to subjective weight and objective weight；
Overall merit module, it is comprehensive for being carried out using whole evaluation index combination attribute mathematicses to the low-voltage power distribution station area
Close and evaluate.
8. low-voltage power distribution station area overall merit device according to claim 7, it is characterised in that the subjective and objective Weight Acquisition
Module obtains subjective weight by G1 expert's enabling legislation to be included：
Whole evaluation indexes are given a mark by multidigit；Classification according to each evaluation index is ranked up；
Calculate the size of weight ratio between adjacent evaluation index；
According to weight of the weight sum for the 1 each evaluation index of principle acquisition；
Marking according to the multidigit to each evaluation index, calculates the average value of each evaluation criterion weight, is commented with obtaining this
The subjective weight of valency index；
And/or included by entropy assessment acquisition objective weight：
Evaluations matrix is determined according to the data of whole evaluation indexes；
The Evaluations matrix is handled to obtain normalized matrix；
Obtain the entropy and coefficient of variation of each evaluation index；
The entropy weight i.e. objective weight of each evaluation index of each evaluation index is obtained according to the entropy and coefficient of variation.
9. low-voltage power distribution station area overall merit device according to claim 8, it is characterised in that the actual weight obtains mould
Block obtains actual weight by following steps to be included：
The subjective weight of each evaluation index and the distance of objective weight are obtained using distance function to obtain subjective weight and visitor
See the distribution coefficient of weight；
The actual weight of each evaluation index is obtained according to subjective weight and its distribution coefficient, objective weight and its distribution coefficient.
10. low-voltage power distribution station area overall merit device according to claim 7, it is characterised in that the overall merit module
Obtaining each grade for commenting index by following steps includes：
Determine the PASCAL evaluation PASCAL grade of Needs index to obtain ordered partition class according to user's request；
Criteria for classification matrix is determined according to the good and bad degree of the ordered partition class and each evaluation index；
Interval composition attributive measure function matrix is estimated according to single item evaluation Criterion Attribute；
The synthesized attribute for obtaining each evaluation index by ranking operation estimates interval；
Confidence level is set to obtain the grade that evaluation index belongs in ordered partition class.
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| CN114024302A (en) * | 2021-09-24 | 2022-02-08 | 深圳市国电科技通信有限公司 | Method and device for evaluating distribution room |
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