CN109657925A - Electric network emergency ability dynamic evaluation method based on grey target theory - Google Patents
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Abstract
The present invention provides a kind of electric network emergency ability dynamic evaluation method based on grey target theory, including extracting object to be evaluated in event experience library and historical data base in the raw data associated of each period；Grey target conversion is carried out after obtaining criterion sequence；Index mode sequences and mode standard sequence gray relative different information space are obtained using the data of the original series of index and the data of standard sequence；Target center coefficient and target center degree of the object on each period are evaluated using the data calculating in obtained gray relative different information space；The grey target contribution coefficient and contribution degree of parameter；Grey target contribution degree is classified, the key index for influencing emergency capability power is found.By being analyzed by grey target contribution degree, each index is analyzed to the influence degree of mode target center degree, to scientifically obtain the stronger index of influence power, targetedly to reinforce index of correlation, promotes the whole emergency capability of power grid to the greatest extent.
Description
Technical field
The invention belongs to field of power systems, in particular to the electric network emergency ability dynamic evaluation side based on grey target theory
Method.
Background technique
It is electric that irreplaceable effect is played in people's production and life with advances in technology with the development of society.
Power grid is nowadays as an infrastructure for maintaining social stability to operate normally, always through people's production and living.But
In recent years, the emergency events such as domestic and international natural calamity, Accidents Disasters take place frequently, and affect the normal fortune of power grid to a certain extent
Row, causes the generation of large area blackout, and daily life is caused to receive serious influence, and social loss is heavy.
For example, beautiful ash moss in 2003 is caused a series of power failure chain reactions to occur, is caused two countries due to circuit local fault
Economic loss it is heavy；Southern ice disaster in 2008 causes electric power facility by serious destruction, when some ground head of district
Between have a power failure, the life of the people is unable to get basic guarantee, and economic loss is huge；Brazil was resulted in due to technical problem in 2018
The generation of large area blackout in range.Dependent part has been reacted in the generation of the above large area blackout to a certain extent
Door in terms of the power emergency ability on deficiency.Therefore, in order to promote emergency capability, enhance the reasonability of decision, to the greatest extent maximum journey
The generation that degree reduces electric power emergency event is lost to caused by power grid, and progress electric network emergency capability evaluation just becomes one and needs
The work of development.
Mostly be at present to treat evaluation object to be analyzed about the research of electric network emergency capability evaluation, provide evaluation of estimate or
Person is ranking results, not can be carried out grade separation and identifies the influence of key factor, and traditional electric network emergency capability evaluation
Mode mostly uses Static Assessment Method, seldom in view of emergency is a dynamic process, plays main make in the different stages
Factor is also different, therefore, can only investigate electric network emergency capability evaluation from unilateral angle, lack comprehensive, comprehensive analysis
Method.
Summary of the invention
In order to solve shortcoming and defect existing in the prior art, the present invention provides the electric network emergencies based on grey target theory
Ability dynamic evaluation method.
Detailed description of the invention
It, below will be to attached drawing needed in embodiment description in order to illustrate more clearly of technical solution of the present invention
It is briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, general for this field
For logical technical staff, without creative efforts, it is also possible to obtain other drawings based on these drawings.
Fig. 1 is the flow diagram of the electric network emergency ability dynamic evaluation method provided by the invention based on grey target theory
Four.
Specific embodiment
For these reasons, the present invention provides a kind of electric network emergency ability dynamic evaluation method based on grey target theory,
The comprehensive evaluation value, classification situation and the ranking results that are evaluated object can be obtained from whole contingency procedure；Shadow can be found again
The key factor of emergency capability is rung, to make up the deficiency of weak link, enhances electric network emergency ability.
To achieve the above object, the present invention provides the following technical solution: a kind of electric network emergency energy based on grey target theory
Power dynamic evaluation method, as shown in Figure 1, the specific steps of the method are as follows:
Step1: electric network emergency effectiveness assessment index system is established, the system is mainly by destination layer, rule layer, indicator layer three
Part forms.Wherein destination layer is first class index layer, includes mono- content of electric network emergency ability basic index system A；Rule layer
It for two-level index layer, is further segmented to destination layer, prevents ability B comprising electric network emergency1, electric network emergency prepare ability B2、
Electric network emergency responding ability B3, electric network emergency recovery capability B4Four contents；Rule layer is three-level indicator layer, is in alignment in then layer
The further division of every capacity index, wherein electric network emergency prevents ability B1It is the complete degree C by laws and regulations11, emergency
Commanding agency quantity C12, emergency preplan complete degree C13, emergency team foundation situation C14Four indices are constituted；Electric network emergency is quasi-
Standby ability B2It is by knowledge for coping with emergencies popularity C21, emergency materials supportability C22, contingent fund put into percentage C23, monitoring
With risk analysis ability C24, communication supportability C25Five indices are constituted；Electric network emergency responding ability B3It is by rescue team
Set ability C31, rescue strength reach situ time C32, news release timeliness C33, resource distribution reasonability C34, responding agencies association
With degree C35Five indices are constituted；Electric network emergency recovery capability B4It is by disposition evaluation capacity C41, incident investigation ability C42, it is kind
Disposing capacity C afterwards43, restoration and reconstruction ability four indices constitute.Thus electric network emergency is carried out on the basis of above-mentioned built index
Capability evaluation；
Step2: the characteristics of according to contingency procedure, being divided into the reasonable period, and from event experience library and history
Lane database extracts in object to be evaluated These parameters in the raw data associated of each period；
Step3: handling achievement data, obtains criterion sequence, and carries out grey target conversion；
Step4: index mode sequences and standard are obtained using the data of the original series of index and the data of standard sequence
Mode sequences gray relative different information space；
Step5: object is evaluated when each using the data calculating in gray relative different information space obtained in Step4
Between target center coefficient and target center degree in section；
Step6: temporal weighting is carried out to the target center degree of each period and is assembled, the overall merit for being evaluated object is obtained
Value；
Step7: being ranked up, be classified and select to the overall situation for being evaluated object according to comprehensive evaluation value excellent, obtains each
The strong and weak situation of evaluation object emergency capability；
Step8: after the power for being respectively evaluated object emergency capability, need further to analyze each index to emergency energy
The percentage contribution of power is convenient for subsequent optimization.Therefore the basis of the contribution reference sequences after Step3 obtains reversal
On, continue to seek each index mode sequences and contribute the different information between reference sequences corresponding element, establishes gray relative difference letter
Cease space；
Step9: the grey target contribution coefficient and contribution degree of parameter；
Step10: grey target contribution degree is classified, and finds the key index for influencing emergency capability power.
Further, it in step Step3, needs to handle achievement data, obtains criterion sequence, and carry out ash
The specific implementation of target conversion is as follows:
Classify to index, is divided into positive (profit evaluation model) index, reverse (cost type) index, designated value or suitable
Medium-sized index three classes.If index is positive (profit evaluation model) index, it is expected that being the bigger the better, then illustrate that the index has maximum pole
Property；If index is reverse (cost type) index, it is expected that the smaller the better, then the index has minimum polarity；If index is
Designated value or moderate type index, then the index has moderate type polarity.Then specific assignment mode are as follows:
(1) it if index has coefficient maximum polarities, is maximized, i.e.,
(2) it if index has minimum polarity, is minimized, i.e.,
(3) if index has moderate value polarity, fetching definite value x00Or average value, i.e.,
x0J=x00Or
Wherein, m expression is evaluated object number；N indicates period number；N indicates evaluation index number；I=1,
2,...,m；J=1,2 ..., n；K=1,2 ..., N.
Sequence x can be obtained by the above method01,x02,...,x0n, which is known as standard sequence, is denoted as x0.It should
Sequence carries out grey target conversionTherefore available standard sequence T (x0)={ 1,
1,...,1}。
Further, it in step Step4, needs to obtain using the data of the original series of index and the data of standard sequence
The specific implementation in index mode sequences and mode standard sequence gray relative different information space is as follows:
If ρ is expressed as resolution ratio, △1The different information between mode sequences and mode standard sequence corresponding element is represented,
That is absolute difference, △maxIndicate maximum absolute difference, △minIndicate minimum absolute difference.Then claim
For mode sequences and mode standard sequence gray relative different information space.
Wherein:
△1={ △ij(tk)|i∈{1,2,...,m},j∈(1,2,...,n),tk∈{t1,t2,...,tN}}(5)
△ij(tk)=| T (x0j)-T(xij(tk)) |=| 1-T (xij(tk))|(6)
Wherein, ρ is used to adjust the difference of incidence coefficient, ρ ∈ (0,1).
Still further, needing to seek to be evaluated target center coefficient and target of the object on each period in step Step5
Heart degree, concrete methods of realizing are as follows:
If γ (x0j(tk),xij(tk)) and γ (x0,xi)(tk) it is expressed as being evaluated object i in tkIndex j when the moment
Target center coefficient and xiIn tkThe target center degree at moment.Wherein:
Further, it in step Step6, needs to carry out temporal weighting to the target center degree of each period to assemble,
Obtain the comprehensive evaluation value for being evaluated object, concrete methods of realizing are as follows:
(1) due to the progress with contingency procedure, the different degree of index can also change, therefore carry out drawing for period
Divide the electric network emergency capability evaluation result that can obtain more accurate data and science.But in contingency procedure, to the side of day part
Emphasis is also different, it is therefore desirable to seek time weight vector, calculation method are as follows:
Wherein, ωkFor time weighting.
The size of " time degree " S indicates that expert is to the attention degree of each timing node in operator assembling process.If S is closer
In 1, indicate that expert more payes attention to node for the previous period；If S is closer to 0, then it represents that expert more payes attention to back segment timing node.
(2) weighting for carrying out time degree is assembled, and calculating is evaluated object yiComprehensive evaluation value:
Further, it in step Step7, needs to be classified target center degree, according to minimum information principle, it may be determined that target
The interval limit of heart degree, calculation method are as follows:
Further, in step Step8, need to seek each index mode sequences and contribution reference sequences corresponding element
Between different information, establish gray relative different information space, concrete methods of realizing are as follows:
(1) △ is set2It represents each index mode sequences and contributes the different information between reference sequences corresponding element, then each index
Mode sequences and contribution reference sequences gray relative different information space are as follows:
Wherein, △2={ △ij(tk)|i∈{1,2,...,m},j∈(1,2,...,n),tk∈{t1,t2,...,tN}}
(16)
△ij(tk)=| T (x0(tk))-T(xij(tk)) |=| γ (x0,xi)(tk)-T(xij(tk))|(17)
Wherein, ρ is used to adjust the difference of incidence coefficient, ρ ∈ (0,1).
Further, in step Step9, the grey target contribution coefficient and contribution degree of parameter are needed, it is specific real
Existing method are as follows:
If γ (xi0(tk),xij(tk)) and γ (x0,xj)(tk) index j is expressed as in tkMoment is evaluated object i's
Contribution coefficient and index j are in tkThe grey target contribution degree at moment.Wherein:
Further, it in step Step10, needs to be classified grey target contribution degree, finding influences emergency capability power
Key index.The same Step7 of its calculation method.
In order to keep technological means of the invention more intuitive, succinct and understandable, below in conjunction with attached drawing, by specific real
Mode is applied the method for the present invention is described in detail.
Present example arbitrarily has chosen tri- areas A, B, C and carries out electric network emergency capability evaluation.
As shown in Figure 1, present example provide it is a kind of based on the electric network emergency ability dynamic evaluation based on grey target theory
Method, specifically includes the following steps:
Step1: electric network emergency effectiveness assessment index system is established, the system is mainly by destination layer, rule layer, indicator layer three
Part forms.Wherein destination layer is first class index layer, includes mono- content of electric network emergency ability basic index system A；Rule layer
It for two-level index layer, is further segmented to destination layer, prevents ability B comprising electric network emergency1, electric network emergency prepare ability B2、
Electric network emergency responding ability B3, electric network emergency recovery capability B4Four contents；Rule layer is three-level indicator layer, is in alignment in then layer
The further division of every capacity index, wherein electric network emergency prevents ability B1It is the complete degree C by laws and regulations11, emergency
Commanding agency quantity C12, emergency preplan complete degree C13, emergency team foundation situation C14Four indices are constituted；Electric network emergency is quasi-
Standby ability B2It is by knowledge for coping with emergencies popularity C21, emergency materials supportability C22, contingent fund put into percentage C23, monitoring
With risk analysis ability C24, communication supportability C25Five indices are constituted；Electric network emergency responding ability B3It is by rescue team
Set ability C31, rescue strength reach situ time C32, news release timeliness C33, resource distribution reasonability C34, responding agencies association
With degree C35Five indices are constituted；Electric network emergency recovery capability B4It is by disposition evaluation capacity C41, incident investigation ability C42, it is kind
Disposing capacity C afterwards43, restoration and reconstruction ability four indices constitute.Thus electric network emergency is carried out on the basis of above-mentioned built index
Capability evaluation；
Step2: the characteristics of according to contingency procedure, being divided into the reasonable period, and from event experience library and history
Lane database extracts in object to be evaluated These parameters in the raw data associated of each period；
According to the general theory of contingency management, contingency management process is generally divided into prevention, preparation, response, restores four ranks
Section, this four-stage have continuity in time, cover the overall process of reply power grid emergency event.It is of the invention based on this
Example chooses prevention (t1), prepare (t2), response (t3) and recovery (t4) four periods carry out electric network emergency ability dynamic comprehensive and comment
Estimate, keep evaluation result more reasonable, the initial data of extraction is shown in Table 1.
1 index initial data of table
Step3: handling achievement data, obtains criterion sequence, and carries out grey target conversion, specifically includes:
Classify to index, is divided into positive (profit evaluation model) index, reverse (cost type) index, designated value or suitable
Medium-sized index three classes.If index is positive (profit evaluation model) index, it is expected that being the bigger the better, then illustrate that the index has maximum pole
Property；If index is reverse (cost type) index, it is expected that the smaller the better, then the index has minimum polarity；If index is
Designated value or moderate type index, then the index has moderate type polarity.Then specific assignment mode are as follows:
(1) it if index has coefficient maximum polarities, is maximized, i.e.,
(2) it if index has minimum polarity, is minimized, i.e.,
(3) if index has moderate value polarity, fetching definite value x00Or average value, i.e.,
x0J=x00
Or
Wherein, m expression is evaluated object number；N indicates period number；N indicates evaluation index number；I=1,
2,...,m；J=1,2 ..., n；K=1,2 ..., N.
Sequence x can be obtained by the above method01,x02,...,x0n, which is known as standard sequence, is denoted as x0.It should
Sequence carries out grey target conversionTherefore available standard sequence T (x0)={ 1,
1,...,1}。
Step4: index mode sequences and standard are obtained using the data of the original series of index and the data of standard sequence
Mode sequences gray relative different information space, specifically includes:
If ρ is expressed as resolution ratio, △1The different information between mode sequences and mode standard sequence corresponding element is represented,
That is absolute difference, △maxIndicate maximum absolute difference, △minIndicate minimum absolute difference.Then claim
For mode sequences and mode standard sequence gray relative different information space.
Wherein: △1={ △ij(tk)|i∈{1,2,...,m},j∈(1,2,...,n),tk∈{t1,t2,...,tN}}(5)
△ij(tk)=| T (x0j)-T(xij(tk)) |=| 1-T (xij(tk))|(6)
Wherein, ρ is used to adjust the difference of incidence coefficient, ρ ∈ (0,1).
After the completion of step Step4, the gray relative different information space of foundation is as shown in table 2:
2 gray relative different information space of table
△max=84；△min=3.
Step5: object is evaluated when each using the data calculating in gray relative different information space obtained in Step4
Between target center coefficient and target center degree in section, specifically include:
If γ (x0j(tk),xij(tk)) and γ (x0,xi)(tk) it is expressed as being evaluated object i in tkIndex j when the moment
Target center coefficient and xiIn tkThe target center degree at moment.Wherein:
According to sensitivity analysis, due to medium resolving effect and good stabilization result, ρ of the present invention takes 0.5, specifically,
Under different scenes, the value of ρ be will be different.
After step Step5, the target center degree of obtained each evaluation object is shown in Table 3:
Each evaluation object target center degree of table 3
Step6: temporal weighting is carried out to the target center degree of each period and is assembled, the overall merit for being evaluated object is obtained
Value, specifically includes:
(1) due to the progress with contingency procedure, the different degree of index can also change, therefore carry out drawing for period
Divide the electric network emergency capability evaluation result that can obtain more accurate data and science.But in contingency procedure, to the side of day part
Emphasis is also different, it is therefore desirable to seek time weight vector, calculation method are as follows:
Wherein, ωkFor time weighting.
The size of " time degree " S indicates that expert is to the attention degree of each timing node in operator assembling process.If S is closer
In 1, indicate that expert more payes attention to node for the previous period；If S is closer to 0, then it represents that expert more payes attention to back segment timing node.
(2) weighting for carrying out time degree is assembled, and the comprehensive evaluation value for being evaluated object yi is calculated:
By consulting relevant expert's opinion, task S takes 0.6 proper the present invention, obtains the value of time weight vector are as follows:
W=(0.3474,0.2722,0.2133,0.1671).
Therefore, after step Step7, obtained comprehensive evaluation value the results are shown in Table 4.
4 comprehensive evaluation value result of table
Step7: being ranked up, be classified and select to the overall situation for being evaluated object according to comprehensive evaluation value excellent, obtains each
The strong and weak situation of evaluation object emergency capability, specifically includes:
According to minimum information principle, it may be determined that the interval limit of target center degree, calculation method are as follows:
Since ρ takes 0.5, γ (x is obtained0,xi)≥0.3333.Target center equilibrium is divided into 7 grades: level-one: [0.9,1], two
Grade: [0.8,0.9), three-level: [0.7,0.8), level Four: [0.6,0.7), Pyatyi: [0.5,0.6), six grades: [0.4,0.5), seven
Grade: [0.3333,0.4).
By table 3, it can be seen that, thus three regional electric network emergency ability levels illustrate, the power grid on three ground in Pyatyi
Emergency capability level is weaker, is reinforced.Therefore, the present invention by analyze should by electric network emergency ability it is strong and weak it is crucial because
Element, in order to targetedly promote emergency capability level.
Step8: after the power for being respectively evaluated object emergency capability, need further to analyze each index to emergency energy
The percentage contribution of power is convenient for subsequent optimization.Therefore the basis of the contribution reference sequences after Step3 obtains reversal
On, continue to seek each index mode sequences and contribute the different information between reference sequences corresponding element, establishes gray relative difference letter
Space is ceased, is specifically included:
(1) △ is set2It represents each index mode sequences and contributes the different information between reference sequences corresponding element, then each index
Mode sequences and contribution reference sequences gray relative different information space are as follows:
Wherein, △2={ △ij(tk)|i∈{1,2,...,m},j∈(1,2,...,n),tk∈{t1,t2,...,tN}}
(16)
△ij(tk)=| T (x0(tk))-T(xij(tk)) |=| γ (x0,xi)(tk)-T(xij(tk))|(17)
Wherein, ρ is used to adjust the difference of incidence coefficient, ρ ∈ (0,1).
After the completion of step Step4, the contribution degree gray relative different information space of foundation is as shown in table 5:
5 contribution degree gray relative different information space of table
△max=84.5707；△min=3.5302.
Step9: the grey target contribution coefficient and contribution degree of parameter specifically include:
If γ (xi0(tk),xij(tk)) and γ (x0,xj)(tk) index j is expressed as in tkMoment is evaluated object i's
Contribution coefficient and index j are in tkThe grey target contribution degree at moment.Wherein:
According to sensitivity analysis, due to medium resolving effect and good stabilization result, ρ of the present invention takes 0.5, specifically,
Under different scenes, the value of ρ be will be different.
After step Step9, the grey target contribution degree for obtaining index is shown in Table 6:
6 evaluation index grey target contribution degree of table
Step10: grey target contribution degree is classified, and finds the key index for influencing emergency capability power, calculation method
Same Step7.
Since ρ takes 0.5, γ (x is obtained0,xi)≥0.3333.Grey target contribution degree equilibrium is divided into 7 grades: [0.9,1],
[0.8,0.9), [0.7,0.8), [0.6,0.7), [0.5,0.6), [0.4,0.5), [0.3333,0.4), and then obtain contribution degree
The big index of degree.
From table 6 we can see that accounting for the index of key factor, to be conducive to targetedly to electric network emergency ability
Reinforced.For example, emergency command mechanism quantity, rescue strength reach grade shared by situ time most in present example
Height is 3 grades, belongs to key influence factor, therefore should reinforce the construction of these two aspects index in work from now on, increase is answered
Anxious commanding agency's quantity and the time for reducing arrival disaster field as far as possible, enhance power grid entirety emergency capability, promotes emergency pipe
The efficiency of decision-making is managed, to utmostly reduce the loss of disaster to the greatest extent.
The above description is only an embodiment of the present invention, is not intended to limit the invention, all in the spirit and principles in the present invention
Within, any modification, equivalent replacement, improvement and so on should all be included in the protection scope of the present invention.
Claims (9)
1. the electric network emergency ability dynamic evaluation method based on grey target theory, which is characterized in that the specific steps of the method are as follows:
Step1: electric network emergency effectiveness assessment index system is established, the system is mainly by destination layer, rule layer, indicator layer three parts
Composition, wherein destination layer is first class index layer, includes mono- content of electric network emergency ability basic index system A；Rule layer is two
Grade indicator layer, is further segmented to destination layer, prevents ability B comprising electric network emergency1, electric network emergency prepare ability B2, power grid
Emergency response capability B3, electric network emergency recovery capability B4Four contents；Rule layer is three-level indicator layer, is in alignment in then layer every
The further division of capacity index, wherein electric network emergency prevents ability B1It is the complete degree C by laws and regulations11, emergency command
Mechanism quantity C12, emergency preplan complete degree C13, emergency team foundation situation C14Four indices are constituted；Electric network emergency prepares energy
Power B2It is by knowledge for coping with emergencies popularity C21, emergency materials supportability C22, contingent fund put into percentage C23, monitoring and wind
Dangerous analysis ability C24, communication supportability C25Five indices are constituted；Electric network emergency responding ability B3It is that energy is disposed by rescue team
Power C31, rescue strength reach situ time C32, news release timeliness C33, resource distribution reasonability C34, responding agencies cooperate with journey
Spend C35Five indices are constituted；Electric network emergency recovery capability B4It is by disposition evaluation capacity C41, incident investigation ability C42, place of dealing with problems arising from an accident
Set ability C43, restoration and reconstruction ability four indices constitute, thus on the basis of above-mentioned built index carry out electric network emergency ability
Assessment；
Step2: the characteristics of according to contingency procedure, being divided into the reasonable period, and from event experience library and historical data
Ku Li extracts in object to be evaluated These parameters in the raw data associated of each period；
Step3: handling achievement data, obtains criterion sequence, and carries out grey target conversion；
Step4: index mode sequences and mode standard are obtained using the data of the original series of index and the data of standard sequence
Sequence gray relative different information space；
Step5: object is evaluated in each period using the data calculating in gray relative different information space obtained in Step4
On target center coefficient and target center degree；
Step6: temporal weighting is carried out to the target center degree of each period and is assembled, the comprehensive evaluation value for being evaluated object is obtained；
Step7: being ranked up, be classified and select to the overall situation for being evaluated object according to comprehensive evaluation value excellent, obtains each evaluation
The strong and weak situation of object emergency capability；
Step8: after the power for being respectively evaluated object emergency capability, need further to analyze each index to emergency capability
Percentage contribution is convenient for subsequent optimization, therefore on the basis of the contribution reference sequences after Step3 obtains reversal,
Continue to seek each index mode sequences and contribute the different information between reference sequences corresponding element, it is empty to establish gray relative different information
Between；
Step9: the grey target contribution coefficient and contribution degree of parameter；
Step10: grey target contribution degree is classified, and finds the key index for influencing emergency capability power.
2. the electric network emergency ability dynamic evaluation method according to claim 1 based on grey target theory, it is characterised in that:
It in step Step3, needs to handle achievement data, obtains criterion sequence, and carry out the tool of grey target conversion
Body implementation is as follows:
Classify to index, be divided into positive index, reverse index, designated value or moderate type index three classes,
If index is positive index, it is expected that being the bigger the better, then illustrate that the index has coefficient maximum polarities；
If index is reverse index, it is expected that the smaller the better, then the index has minimum polarity；
If index is designated value or moderate type index, which has moderate type polarity, then specific assignment mode are as follows:
(1) it if index has coefficient maximum polarities, is maximized, i.e.,
(2) it if index has minimum polarity, is minimized, i.e.,
(3) if index has moderate value polarity, fetching definite value x00Or average value, i.e.,
x0j=x00Or
Wherein, m expression is evaluated object number；N indicates period number；N indicates evaluation index number；I=1,2 ..., m；j
=1,2 ..., n；K=1,2 ..., N；
Sequence x can be obtained by the above method01,x02,...,x0n, which is known as standard sequence, is denoted as x0, by the sequence into
Row ash target conversionTherefore available standard sequence T (x0)={ 1,1 ..., 1 }.
3. the electric network emergency ability dynamic evaluation method according to claim 1 based on grey target theory, it is characterised in that:
In step Step4, need to obtain index mode sequence using the data of the original series of index and the data of standard sequence
The specific implementation in column and mode standard sequence gray relative different information space is as follows:
If ρ is expressed as resolution ratio, △1The different information between mode sequences and mode standard sequence corresponding element is represented, i.e., absolutely
Difference, △maxIndicate maximum absolute difference, △minIt indicates minimum absolute difference, then claims
△1 GR=(△1, ρ, △max,△min) (4) be mode sequences and mode standard sequence gray relative different information space,
Wherein:
△1={ △ij(tk)|i∈{1,2,...,m},j∈(1,2,...,n),tk∈{t1,t2,...,tN(5),
△ij(tk)=| T (x0j)-T(xij(tk)) |=| 1-T (xij(tk)) | (6),
Wherein, ρ is used to adjust the difference of incidence coefficient, ρ ∈ (0,1).
4. the electric network emergency ability dynamic evaluation method according to claim 1 based on grey target theory, it is characterised in that:
It in step Step5, needs to seek to be evaluated target center coefficient and target center degree of the object on each period, implements
Method are as follows:
If γ (x0j(tk),xij(tk)) and γ (x0,xi)(tk) it is expressed as being evaluated object i in tkThe target of index j when the moment
Feel concerned about several and xiIn tkThe target center degree at moment, in which:
5. the electric network emergency ability dynamic evaluation method according to claim 1 based on grey target theory, it is characterised in that:
In step Step6, needs to carry out temporal weighting to the target center degree of each period to assemble, obtain being evaluated object
Comprehensive evaluation value, concrete methods of realizing are as follows:
(1) due to the progress with contingency procedure, the different degree of index can also change, therefore carry out the division energy of period
Obtain more accurate data and science electric network emergency capability evaluation as a result, but in contingency procedure, to the emphasis of day part
It is also different, it is therefore desirable to seek time weight vector, calculation method are as follows:
Wherein, ωkSize for time weighting, " time degree " S indicates attention of the expert to each timing node in operator assembling process
Degree, if S closer to 1, indicates that expert more payes attention to node for the previous period；If S is closer to 0, then it represents that after expert more payes attention to
Section timing node,
(2) weighting for carrying out time degree is assembled, and calculating is evaluated object yiComprehensive evaluation value:
6. the electric network emergency ability dynamic evaluation method according to claim 1 based on grey target theory, it is characterised in that:
Further, it in step Step7, needs to be classified target center degree, according to minimum information principle, it may be determined that target center degree
Interval limit, calculation method are as follows:
7. the electric network emergency ability dynamic evaluation method according to claim 1 based on grey target theory, it is characterised in that:
In step Step8, needs to seek each index mode sequences and contribute the different information between reference sequences corresponding element, build
Vertical gray relative different information space, concrete methods of realizing are as follows:
(1) △ is set2It represents each index mode sequences and contributes the different information between reference sequences corresponding element, then each index mode
Sequence and contribution reference sequences gray relative different information space are as follows:
Wherein, △2={ △ij(tk)|i∈{1,2,...,m},j∈(1,2,...,n),tk∈{t1,t2,...,tN(16),
△ij(tk)=| T (x0(tk))-T(xij(tk)) |=| γ (x0,xi)(tk)-T(xij(tk)) | (17),
Wherein, ρ is used to adjust the difference of incidence coefficient, ρ ∈ (0,1).
8. the electric network emergency ability dynamic evaluation method according to claim 1 based on grey target theory, it is characterised in that:
In step Step9, the grey target contribution coefficient and contribution degree of parameter, concrete methods of realizing are needed are as follows:
If γ (xi0(tk),xij(tk)) and γ (x0,xj)(tk) it is expressed as the contribution that index j is evaluated object i at the tk moment
Coefficient and index j are in tkThe grey target contribution degree at moment, in which:
9. the electric network emergency ability dynamic evaluation method according to claim 1 based on grey target theory, it is characterised in that:
It in step Step10, needs to be classified grey target contribution degree, finds the key index for influencing emergency capability power,
The same Step7 of calculation method.
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| CN113837644A (en) * | 2021-09-30 | 2021-12-24 | 中国人民解放军战略支援部队航天工程大学 | Equipment combat effectiveness and contribution rate integrated evaluation method based on grey correlation |
| CN117574115A (en) * | 2024-01-16 | 2024-02-20 | 中国空气动力研究与发展中心计算空气动力研究所 | Wind tunnel test research data acquisition, analysis and evaluation method, system and related equipment |
| CN117574115B (en) * | 2024-01-16 | 2024-03-22 | 中国空气动力研究与发展中心计算空气动力研究所 | Wind tunnel test research data acquisition, analysis and evaluation method, system and related equipment |
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