CN106779267A - A kind of electric power system model based on multi-layer Fuzzy method and quality testing method - Google Patents
A kind of electric power system model based on multi-layer Fuzzy method and quality testing method Download PDFInfo
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Abstract
The present invention provides a kind of electric power system model based on multi-layer Fuzzy method and quality testing method, by obtaining power system basic model and data, obtains power system Back ground Information；Set up the mutiple-stage model index factor collection of power system Back ground Information；Weight distribution is carried out to mutiple-stage model index factor collection, mutiple-stage model index system is obtained；Fuzzy mathematics calculating is carried out to mutiple-stage model index system, Fuzzy comprehensive evaluation result is obtained；And then power system basic model and data are estimated.Method proposed by the present invention effectively prevent Back ground Information influence of the missing to overall data quality evaluation, solve state estimation can not flexibly and multi-angle evaluation power system basic data quality present situation；For electric power system model and the quality of data provide accurate and effectively evaluating result and amendment scheme, integrality, correctness and the accuracy of archetype and data are improved；And then ensure that the stable operation of power system.
Description
Technical field
The present invention relates to power system automatic field, and in particular to a kind of electric power system model based on multi-layer Fuzzy method with
Quality testing method.
Background technology
With the increasingly complication of modern power systems, the power network scale for constantly expanding is proposed to management and running and control system
Requirements at the higher level.The important foundation for realizing dispatching automation of electric power systems be obtain or build more completely with accurate electric power
The data such as system model, parameter and measurement, so that dispatch automated system draws accurate on-line analysis and processed offline knot
Really, it is ensured that power generation is safe efficient and economical operation.Data needed for electric power scheduling automatization system relate generally to base
Plinth data, monitoring data, planning data and assay class data.The quality of the quality of data, can the system of directly affecting
Accurate and Effec-tive Function, operation of power networks state, quick diagnosis failure etc. can be correctly grasped, be indispensable power scheduling
Important support.Wherein, directly participate in on-line analysis calculate based on model and metric data.For a long time, energy
Acquisition system (EMS, Energy Management System) is more using Power system state estimation to electric network model sum
According to the amount that collection is gathered with supervisor control (SCADA, Supervisory Control and Data Acquisition)
Survey carries out model checking and data identification, is used to reflect and lifted the quality of data on basis, meanwhile, state estimation calculates knot
Fruit is also for powernet analysis provides more reasonably data.
Currently carried out with the evaluation Main Basiss state estimation result of metric data quality for model.However, existing shape
State estimates that evaluation index is more single, and its analysis result is confined to evaluate the qualification rate of metric data, it is impossible to comprehensively reflection
The model of power system and the quality of data of parameter, data difference degree is not high, it is impossible to accurately and precisely react power system
Basic data quality, it is impossible to distinguish integrality, correctness and the accuracy of model and metric data.
The content of the invention
In view of this, the present invention is provided a kind of electric power system model based on multi-layer Fuzzy method and quality testing side
Method, the method effectively prevent basic data influence of the missing to quality testing, solve state estimation can not flexibly and
Multi-angle evaluates the present situation of power system basic data quality；For electric power system model and the quality of data provide accurate and have
The evaluation result and amendment scheme of effect, improve integrality, correctness and the accuracy of archetype and data；And then protect
The stable operation of power system is demonstrate,proved.
The purpose of the present invention is achieved through the following technical solutions：
A kind of electric power system model based on multi-layer Fuzzy method and quality testing method, methods described include following step
Suddenly：
Step 1. obtains power system basic model and data, obtains power system Back ground Information；
Step 2. sets up the mutiple-stage model index factor collection of the power system Back ground Information；
Mutiple-stage model index factor collection is stated described in step 3. pair carries out weight distribution, obtains the mutiple-stage model index body
System；
The step 4. pair mutiple-stage model index system carries out fuzzy mathematics calculating, obtains Fuzzy comprehensive evaluation result；
Step 5. is estimated according to the Fuzzy comprehensive evaluation result to power system basic model and data.
Preferably, the step 1 includes：
1-1. obtains the power system basic model；The power system basic model be computation model and its by electric power
The device parameter generation of system physical model；
Wherein, the equipment of the power system physical model includes：Reference voltage, control area, voltage class, generating
It is unit, transformer station or power plant, breaker, disconnecting switch, earthed switch, bus, exchange line segment, transformer, negative
Lotus, shunt capacitance or reactor, series compensator, transverter, direct current line segment, DC flat-wave reactor, DC filtering
Device；
The power system basic model includes electric connecting relation and device parameter：Reference voltage, control area, voltage
It is grade, generating set, transformer station or power plant, logical node, topological island, bus, exchange line segment, transformer, negative
Lotus, shunt capacitance or reactor, series compensator, transverter, direct current line segment, DC flat-wave reactor, DC filtering
Device；
1-2. obtains the power system basic data；The power system basic data includes power system measurement information；
Wherein, the power system measurement information passes through SCADA system, WAMS or PMU physical quantity harvesters
Obtain and it includes：Remote measurement amount, remote signalling amount, remote regulating amount, remote control amount information, PMU data and fault recorder data.
Preferably, the step 2 includes：
2-1. will be divided into multistage evaluation index for evaluating the index of the power system Back ground Information；
One-level evaluation index in the multistage evaluation index is divided into model class index, parameter class index and measurement by 2-2.
Class index；
Each one-level evaluation index is carried out multistage permutation and combination by 2-3., obtains two grades under each one-level evaluation index
Index；
Two-level appraisement index in the model class index includes topological relation accuracy data information and model integrity number
It is believed that breath；
Two-level appraisement index in the parameter class index includes the parameter accuracy data information of each power equipment；
The two-level appraisement index measured in class index includes accuracy data information, the remote signalling amount to the collection of remote measurement amount
Correctness data message, the consistent data information for measuring the time, the accuracy data information and error in measurement number that measure collection
It is believed that breath；
Each two-level appraisement index is carried out multistage permutation and combination by 2-4., obtains the three-level under each two-level appraisement index
Index, continues to segment, until obtaining the mutiple-stage model index factor collection to the three-level index.
Preferably, the step 3 includes：
According to power system history run operating mode, the model class for stating mutiple-stage model index factor concentration is referred to successively
Mark, parameter class index and measurement class index carry out weight distribution, obtain the mutiple-stage model index system.
Preferably, the step 4 includes：
4-1. judges the mutiple-stage model index system；
4-2. is calculated one-level evaluation vector and single factor judgment matrix；
4-3. distributes weight according to the importance of each factor, obtains one-level and judges vector and two grades of judge vectors；
4-4. obtains Fuzzy comprehensive evaluation result.
Preferably, the step 4-1 includes：
A. by the index factor collection U={ u in the mutiple-stage model index system1,u2,…,unIt is divided into s according to its attribute
Individual sub- set of factors U1,U2..., Us, then have：
In formula (1), UiIt is i-th index factor collection, andUjIt is jth
Individual index factor collection；N is the number of the index factor that index factor is concentrated；
B. to set of factors U each describediComprehensive Evaluation is made respectively；If V={ v1,v2,…,vmBe Comment gathers, then obtain
UiIn weight distribution of each factor relative to V be
Preferably, the step 4-2 includes：
C. it is calculated one-level evaluation vector Bi：
Bi=Ai·Ri=[bi1,bi2,…,bim], i=1,2 ..., s (2)
In formula (2), RiIt is simple element evaluation vector；M is the number of the element b in one-level evaluation vector；
D. it is calculated single factor judgment matrix R：
Preferably, the step 4-3 includes：
Importance distribution weight according to each factor, obtains one-level and judges vector A=[a1,a2,…,as] and two grades judge to
Amount B=AR=[b1,b2,…,bm]。
Preferably, the step 4-4 includes：
4-4. obtains Fuzzy comprehensive evaluation result.
It is calculated Fuzzy comprehensive evaluation result Z：
Z=BF (4)
In formula (4), F is evaluation interval vector.
It can be seen from above-mentioned technical scheme that, the invention provides a kind of electric power system model based on multi-layer Fuzzy method with
Quality testing method, by obtaining power system basic model and data, obtains power system Back ground Information；Set up
The mutiple-stage model index factor collection of power system Back ground Information；Weight distribution is carried out to mutiple-stage model index factor collection,
Obtain mutiple-stage model index system；Fuzzy mathematics calculating is carried out to mutiple-stage model index system, fuzzy synthesis is obtained and is commented
Estimate result；And then power system basic model and data are estimated.Method proposed by the present invention effectively prevent basis
Influence of the loss of learning to quality testing, solving state estimation can not flexibly and multi-angle evaluates the basic number of power system
According to the present situation of quality；For electric power system model and the quality of data provide accurate and effectively evaluating result and amendment scheme,
Improve integrality, correctness and the accuracy of archetype and data；And then ensure that the stable operation of power system.
With immediate prior art ratio, the present invention provide technical scheme there is following excellent effect：
1st, in technical scheme provided by the present invention, using the method for multi-layer Fuzzy overall merit, to power system basis
Model, parameter and the quality of data are tested and evaluation, set up data evaluation system, effectively compensate for power system shape
The problems such as state estimates the unicity and data difference degree not high to basic data quality evaluation.Greatly improve to basis
The accuracy of data evaluation, integrality with it is comprehensive, have very strong flexibility and practicality.
2nd, technical scheme provided by the present invention, effectively prevent shadow of the Back ground Information missing to overall data quality evaluation
Ring, solve state estimation can not flexibly and multi-angle evaluation power system basic data quality present situation；It is power system mould
Type provides accurate and effectively evaluating result and amendment scheme with the quality of data, improves archetype complete with data
Property, correctness and accuracy；And then ensure that the stable operation of power system.
3rd, the technical scheme that the present invention is provided, is widely used in power system, with significant social benefit and
Economic benefit.
Brief description of the drawings
Fig. 1 is the flow of a kind of electric power system model based on multi-layer Fuzzy method of the invention and quality testing method
Figure；
The schematic flow sheet of the step of Fig. 2 is evaluation method of the invention 1；
The schematic flow sheet of the step of Fig. 3 is evaluation method of the invention 2；
The schematic flow sheet of the step of Fig. 4 is evaluation method of the invention 4.
Specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out clear, complete
Ground description, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.Base
In embodiments of the invention, those of ordinary skill in the art obtained under the premise of creative work is not made it is all its
His embodiment, belongs to the scope of protection of the invention.
As shown in figure 1, the present invention provides a kind of electric power system model based on multi-layer Fuzzy method and quality testing side
Method, comprises the following steps：
Step 1. obtains power system basic model and data, obtains power system Back ground Information；
Step 2. sets up the mutiple-stage model index factor collection of power system Back ground Information；
Step 3. pair states mutiple-stage model index factor collection and carries out weight distribution, obtains mutiple-stage model index system；
Step 4. carries out fuzzy mathematics calculating to mutiple-stage model index system, obtains Fuzzy comprehensive evaluation result；
Step 5. is estimated according to Fuzzy comprehensive evaluation result to power system basic model and data, draws assessment
Report；
After step 5, the present embodiment also includes：According to assessment report, power system is modified, to ensure electricity
The stable operation of Force system.
As shown in Fig. 2 step 1 includes：
1-1. obtains power system basic model；Power system basic model be computation model and its by power system physics
The device parameter generation of model；
Wherein, the equipment of power system physical model includes：Reference voltage, control area, voltage class, generating set,
Transformer station or power plant, breaker, disconnecting switch, earthed switch, bus, exchange line segment, transformer, load and
Connection electric capacity or reactor, series compensator, transverter, direct current line segment, DC flat-wave reactor, DC filter；
Power system basic model includes electric connecting relation and device parameter：Reference voltage, control area, voltage class,
Generating set, transformer station or power plant, logical node, topological island, bus, exchange line segment, transformer, load and
Connection electric capacity or reactor, series compensator, transverter, direct current line segment, DC flat-wave reactor, DC filter；
1-2. obtains power system basic data；Power system basic data includes power system measurement information；
Wherein, power system measurement information by SCADA system, WAMS or PMU physical quantitys harvester obtain and
It includes：Remote measurement amount (analog quantity), remote signalling amount (quantity of state), remote regulating amount, remote control amount information, PMU data and
Fault recorder data；Physical model information can generate computation model, and it combines measurement collection capacity and is used to participate in power system
On-line analysis is calculated with off-line analysis.
As shown in figure 3, step 2 includes：
2-1. will be divided into multistage evaluation index for evaluating the index of power system Back ground Information；
One-level evaluation index in multistage evaluation index is divided into model class index, parameter class index by 2-2. by importance
And measure class index；
Each one-level evaluation index is carried out multistage permutation and combination by 2-3., obtains the two-level index under each one-level evaluation index；
Two-level appraisement index in model class index includes that topological relation accuracy data information and model integrity data are believed
Breath；Wherein model classification can include the two-level appraisement index of reflection topological relation accuracy, model integrity etc.；Parameter class
The parameter accuracy information for characterizing different power equipments can not included as two-level appraisement index；Measurement classification can be included and is directed to
The accuracy of analog quantity (remote measurement) collection, the correctness of quantity of state (remote signalling), the uniformity for measuring the time, measurement are adopted
The two-level index that the precision of collection, error in measurement are evaluated.All kinds of two-level index can continue classification, the electric power that generation is refined layer by layer
System-based data multilevel evaluation index.Multistage evaluation index ultimately generates evaluation index set of factors；
Two-level appraisement index in parameter class index includes the parameter accuracy data information of each power equipment；
Measure class index in two-level appraisement index include to remote measurement amount collection accuracy data information, remote signalling amount it is correct
Property data message, measure the time consistent data information, measure collection accuracy data information and error in measurement data letter
Breath；
Each two-level appraisement index is carried out multistage permutation and combination by 2-4., obtains the three-level index under each two-level appraisement index, right
Three-level index continues to segment, until obtaining mutiple-stage model index factor collection.
Wherein, step 3 includes：
According to power system history run operating mode, successively to stating the model class index of mutiple-stage model index factor concentration, joining
Several classes of index and measurement class index carry out weight distribution, obtain mutiple-stage model index system.
As shown in figure 4, step 4 includes：
4-1. judges mutiple-stage model index system；
4-2. is calculated one-level evaluation vector and single factor judgment matrix；
4-3. distributes weight according to the importance of each factor, obtains one-level and judges vector and two grades of judge vectors；
4-4. obtains Fuzzy comprehensive evaluation result.
Wherein, step 4-1 includes：
A. by the index factor collection U={ u in mutiple-stage model index system1,u2,…,unIt is divided into s son according to its attribute
Set of factors U1,U2..., Us, then have：
In formula (1), UiIt is i-th index factor collection, andUjIt is jth
Individual index factor collection；N is the number of the index factor that index factor is concentrated；
B. to each set of factors UiComprehensive Evaluation is made respectively；If V={ v1,v2,…,vmBe Comment gathers, then obtain UiIn
Weight distribution of each factor relative to V be
Wherein, step 4-2 includes：
C. it is calculated one-level evaluation vector Bi：
Bi=Ai·Ri=[bi1,bi2,…,bim], i=1,2 ..., s (2)
In formula (2), RiIt is simple element evaluation vector；M is the number of the element b in one-level evaluation vector；
D. it is calculated single factor judgment matrix R：
Wherein, step 4-3 includes：
Importance distribution weight according to each factor, obtains one-level and judges vector A=[a1,a2,…,as] and two grades judge to
Amount B=AR=[b1,b2,…,bm]。
9th, method as claimed in claim 8, it is characterised in that step 4-4 includes：
4-4. obtains Fuzzy comprehensive evaluation result.
It is calculated Fuzzy comprehensive evaluation result Z：
Z=BF (4)
In formula (4), F is evaluation interval vector.
To sum up, in newly-established indicator evaluation system, the weight of fuzzy evaluating matrix and distribution according to lower floor's index
Fuzzy mathematics computing is carried out, the Evaluations matrix of upper strata index is obtained.Analyzed by matrix operation, obtained on power train
The fuzzy overall evaluation result of calculation of " model-parameter-measurement " three major types basic data of uniting.According to default comment area
Between, obtain the fuzzy synthesis score and assessment report of evaluation object；Finally, according to assessment report, power system is entered
Row amendment, to ensure the stable operation of power system.
The above embodiments are merely illustrative of the technical solutions of the present invention rather than its limitations, although with reference to above-described embodiment to this
Invention has been described in detail, and those of ordinary skill in the art can still enter to specific embodiment of the invention
Row modification or equivalent, and these are without departing from any modification of spirit and scope of the invention or equivalent, its is equal
Applying within pending claims of the invention.
Claims (9)
1. a kind of electric power system model based on multi-layer Fuzzy method and quality testing method, it is characterised in that described
Method is comprised the following steps：
Step 1. obtains power system basic model and data, obtains power system Back ground Information；
Step 2. sets up the mutiple-stage model index factor collection of the power system Back ground Information；
The step 3. pair mutiple-stage model index factor collection carries out weight distribution, obtains the mutiple-stage model index body
System；
The step 4. pair mutiple-stage model index system carries out fuzzy mathematics calculating, obtains Fuzzy comprehensive evaluation result；
Step 5. is estimated according to the Fuzzy comprehensive evaluation result to power system basic model and data.
2. the method for claim 1, it is characterised in that the step 1 includes：
1-1. obtains the power system basic model；The power system basic model be computation model and its by electric power
The equipment generation of system physical model；
Wherein, the equipment of the power system physical model includes：Reference voltage, control area, voltage class, generating
It is unit, transformer station or power plant, breaker, disconnecting switch, earthed switch, bus, exchange line segment, transformer, negative
Lotus, shunt capacitance or reactor, series compensator, transverter, direct current line segment, DC flat-wave reactor, DC filtering
Device；
The power system basic model includes electric connecting relation and device parameter：Reference voltage, control area, voltage
It is grade, generating set, transformer station or power plant, logical node, topological island, bus, exchange line segment, transformer, negative
Lotus, shunt capacitance or reactor, series compensator, transverter, direct current line segment, DC flat-wave reactor, DC filtering
Device；
1-2. obtains the power system basic data；The power system basic data includes power system measurement information；
Wherein, the power system measurement information passes through SCADA system, WAMS or PMU physical quantity harvesters
Obtain and it includes：Remote measurement amount, remote signalling amount, remote regulating amount, remote control amount information, PMU data and fault recorder data.
3. the method for claim 1, it is characterised in that the step 2 includes：
2-1. will be divided into multistage evaluation index for evaluating the index of the power system Back ground Information；
One-level evaluation index in the multistage evaluation index is divided into model class index, parameter class index and measurement by 2-2.
Class index；
Each one-level evaluation index is carried out multistage permutation and combination by 2-3., obtains two grades under each one-level evaluation index
Index；
Two-level appraisement index in the model class index includes topological relation accuracy data information and model integrity number
It is believed that breath；
Two-level appraisement index in the parameter class index includes the parameter accuracy data information of each power equipment；
The two-level appraisement index measured in class index includes accuracy data information, the remote signalling amount to the collection of remote measurement amount
Correctness data message, the consistent data information for measuring the time, the accuracy data information and error in measurement number that measure collection
It is believed that breath；
Each two-level appraisement index is carried out multistage permutation and combination by 2-4., obtains the three-level under each two-level appraisement index
Index, continues to segment, until obtaining the mutiple-stage model index factor collection to the three-level index.
4. the method for claim 1, it is characterised in that the step 3 includes：
According to power system history run operating mode, the model class for stating mutiple-stage model index factor concentration is referred to successively
Mark, parameter class index and measurement class index carry out weight distribution, obtain the mutiple-stage model index system.
5. the method for claim 1, it is characterised in that the step 4 includes：
4-1. judges the mutiple-stage model index system；
4-2. is calculated one-level evaluation vector and single factor judgment matrix；
4-3. distributes weight according to the importance of each factor, obtains one-level and judges vector and two grades of judge vectors；
4-4. obtains Fuzzy comprehensive evaluation result.
6. method as claimed in claim 5, it is characterised in that the step 4-1 includes：
A. by the index factor collection U={ u in the mutiple-stage model index system1,u2,…,unIt is divided into s according to its attribute
Individual sub- set of factors U1,U2..., Us, then have：
In formula (1), UiIt is i-th index factor collection, andUjIt is jth
Individual index factor collection；N is the number of the index factor that index factor is concentrated；
B. to set of factors U each describediComprehensive Evaluation is made respectively；If V={ v1,v2,…,vmBe Comment gathers, then obtain
UiIn weight distribution of each factor relative to V be
7. method as claimed in claim 6, it is characterised in that the step 4-2 includes：
C. it is calculated one-level evaluation vector Bi：
Bi=Ai·Ri=[bi1,bi2,…,bim], i=1,2 ..., s (2)
In formula (2), RiIt is simple element evaluation vector；M is the number of the element b in one-level evaluation vector；
D. it is calculated single factor judgment matrix R：
8. method as claimed in claim 7, it is characterised in that the step 4-3 includes：
Importance distribution weight according to each factor, obtains one-level and judges vector A=[a1,a2,…,as] and two grades judge to
Amount B=AR=[b1,b2,…,bm]。
9. method as claimed in claim 8, it is characterised in that the step 4-4 includes：
4-4. obtains Fuzzy comprehensive evaluation result.
It is calculated Fuzzy comprehensive evaluation result Z：
Z=BF (4)
In formula (4), F is evaluation interval vector.
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| CN110119859A (en) * | 2018-02-05 | 2019-08-13 | 南京易司拓电力科技股份有限公司 | A kind of equipment state assessment method based on big data |
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Application publication date: 20170531 |