CN109063950A - A kind of dynamic time warping association appraisal procedure towards intelligent distribution network controllability - Google Patents
A kind of dynamic time warping association appraisal procedure towards intelligent distribution network controllability Download PDFInfo
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Abstract
The invention proposes a kind of controllability dynamic time warpings of intelligent distribution network to be associated with appraisal procedure, comprising the following steps: step 1: the building of intelligent distribution network controllability evaluation index system；Step 2: the scoring of assessment data acquisition and index；Step 3: the weight assignment of evaluation index；Step 4: the controllability DTW of intelligent distribution network is associated with assessment；Step 5: the controllability DTW of intelligent distribution network is associated with assessment.A variety of key factors of the comprehensive analyzing influence power distribution network controllability of the present invention complete the building of intelligent distribution network controllability evaluation index system, so that evaluation index system is more scientific and comprehensive.
Description
Technical field
The present invention relates to the controllability evaluation areas of intelligent distribution network, and in particular to a kind of dynamic time warping association analysis
Intelligent distribution network controllability appraisal procedure.
Background technique
With the large-scale grid connection of distributed generation resource (DG), distributed energy storage device (DESS) it is extensive access and it is electronic
The rapid development of automobile (EV), while bringing huge improvement to social environment, since the voltage of load bus is lifted, switch
Device frequently acts the power quality problems such as the harmonic wave of generation and brings huge challenge to power distribution network.Intelligence is matched at the same time
Power grid comes into being, and intelligent distribution network can rapidly perceive the operating status of power distribution network, active control and management distribution in real time
Various distributed generation resource, energy storage device and controllable burden in net.In order to ensure the safe and reliable operation of power distribution network, it is necessary to intelligence
The controllability of energy power distribution network carries out comprehensive, accurately comprehensive assessment.
Currently, research both domestic and external is concentrated mainly on intelligent distribution network in terms of intelligent power distribution Running State assessment
In terms of operational safety, reliable, economy.The controllability of certain distributed generation resources is poor in intelligent distribution network, energy storage device, controllable
Load is also required to unified control, therefore in order to give full play to the controllability of intelligent distribution network, distributed generation resource, to intelligent power distribution
It is imperative that net carries out controllability Study.In order to realize intelligent distribution network controllability comprehensive assessment, the present invention proposes a kind of general
Evaluation index system and appraisal procedure.In order to solve the problems, such as intelligent distribution network controllability comprehensive assessment, it is proposed that solution party
Case is as follows: 1) a variety of key factors of analyzing influence power distribution network stable operation, completion intelligent distribution network controllability assessment refer to comprehensively
The building of mark system, so that evaluation index system is more scientific and comprehensive；2) tax of weight is completed using analytic hierarchy process (AHP)
Value, improves the reasonability and objectivity of evaluation index system；3) finally using dynamic time warping method to distributed generation resource into
Row controllability comprehensive assessment carries out controllability grade assessment by analyzing the similarity of index to be assessed and standard index, most
Comprehensive assessment is carried out to the controllability of intelligent distribution network eventually.
Summary of the invention
In order to make up the deficiency in existing assessment face, the present invention provides a kind of controllability dynamic time of intelligent distribution network is curved
Qu Guanlian appraisal procedure.The technical solution of the present invention is as follows:
A kind of controllability dynamic time warping association appraisal procedure of intelligent distribution network, comprising the following steps: step 1: intelligence
It can the building of power distribution network controllability evaluation index system；Step 2: the scoring of assessment data acquisition and index；Step 3: evaluation index
Weight assignment；Step 4: the controllability DTW of intelligent distribution network is associated with assessment；Step 5: the controllability DTW of intelligent distribution network is closed
Connection assessment.
Further, the step 1 specifically:
Step 1-1: fully consider distributed generation resource real-time power output, the state-of-charge of energy-accumulating power station, power factor, electricity
After pressure deviates these influence factors to the influence mode and influence degree of intelligent distribution network controllability, forming intelligent distribution network can
Control property evaluation index system, including distributed electrical source utilization rate index, energy-accumulating power station state-of-charge index, power factor specification and
Variation index；
Step 1-2: according to intelligent distribution network controllability evaluation index system, master sample sequence is established, standard sample is set
This is X1=[x11,x12,x13], it respectively corresponds and contributes in real time for distributed generation resource: distributed electrical source utilization rate or energy-accumulating power station
State-of-charge；Control ability that distributed generation resource is idle: power factor；Voltage regulation capability: variation, index calculation is such as
Following formula:
Distributed electrical source utilization rate index:
Energy-accumulating power station state-of-charge index:
Power factor specification:
Variation index: Δ Ui=| 1-Ui|
In above formula, PDG,iThe active power that distributed generation resource or energy-accumulating power station issue, QDG,iDistributed generation resource or energy-accumulating power station
The reactive power for absorbing or issuing, SN,iThe rated capacity of distributed generation resource or energy storage power station grid connection inverter, EC,iEnergy-accumulating power station
Residual capacity, UiGrid entry point standard voltage value；
Step 1-3: master sample baseline impact scale sequence A is established1=[a11,a12,a13], while A1It is commented as final
Estimate the first row of sample matrix A；a11For the utilization rate index of distributed generation resource, a12For power factor specification, a13For variation
Index.
Further, the step 2 specifically:
Step 2-1: the master sample sequence middle finger target calculation according to step 1, acquisition intelligent distribution network can
Data needed for control property is assessed form reference data sample sequence and data sample sequence to be assessed；Pass through score function standard sample
Originally it is 1 that master sample scoring, which can be obtained, and each index score function is shown below:
Distributed electrical source utilization rate score function: ai10≤η≤1=1- η
Energy-accumulating power station state-of-charge score function:
Power factor score function:
Variation score function:
Step 2-2: each evaluation index is formed by the data acquired, and scoring letter is established according to the influence factor of each index
Number, is scored using score function to reference sample and sample to be assessed.
Further, the step 3 specifically:
Using AHP index weights assignment method can to distributed electrical source utilization rate index in evaluation index system, power because
Number index, variation index carry out subjective assignment；
Step 3-1: it according to each evaluation index to the influence degree of intelligent distribution network controllability, is compared to each other and obtains each index
Importance degree, choose and compare the size of scale, and then form multilevel iudge matrix；
Step 3-2: by comparator matrix two-by-two obtain matrix maximum eigenvalue and its corresponding feature vector, complete one
The verification of cause property, chooses again if being unsatisfactory for consistency desired result and compares scale；
Step 3-3: real using the maximum eigenvalue and its feature vector sought to the judgment matrix for meeting above-mentioned condition
Row normalized completes subjective weight assignment；Master sample distance sequence, reference using subjective weight, after finding out weighting
Sample distance sequence and sample distance sequence to be assessed.
Further, the step 4 specifically:
The minimum accumulated distance of two groups of sample sequences is solved by calculating, and minimum accumulated distance is recycled to measure two samples
Similarity degree between this；
Step 4-1: it calculates distance matrix: the Europe of corresponding element in two sample sequences can be obtained using following formula calculation formula
Formula distance lambdaij,
In formula, u and v respectively indicate two sample sequences for needing to compare, and corresponding element can use i=2,3 ..., m and j
=2,3 ..., n；Euclidean distance is arranged according to certain rules can be obtained distance matrix and is shown below:
Step 4-2: calculate accumulation distance matrix: calculation method is shown below, and obtains minimum by accumulation distance matrix
Deflection distance is associated with matching factor；D (i, j) indicates the minimum bend distance that (i, j) is arrived from (1,1), the value of D (m, n) i.e. two
The minimum bend distance of a sample sequence, reflects the similarity degree of two samples.
Step 4-3: by reference to the association matching factor C of sample sequenceiTo determine the range of different controllability grades；And
By sample sequence to be assessed and the association matching factor of master sample sequence compared with above range, sample to be assessed is finally obtained
Controllability grade.
Further, the step 5 specifically:
The association matching factor of sample to be assessed is calculated using DTW association appraisal procedure, and forms each distributed electrical
Association matching factor in the case of source and energy-accumulating power station different loads；According to Distributed Generation in Distribution System obtained above and storage
Can power station association matching factor, in conjunction with influence intelligent distribution network controllability key element it is found that distributed generation resource and storage
The relative capacity in energy power station has vital influence to controllability, it follows that the controllability of intelligent distribution network is assessed；
Calculation formula is shown below:
In formula, n is the number of distributed generation resource and energy-accumulating power station in intelligent distribution network, STFor distributed generation resource and energy storage electricity
The total capacity stood, SiFor distributed generation resource or the capacity of energy-accumulating power station, CiTo be associated with matching factor accordingly.
Beneficial effect
Compared with the immediate prior art, the present invention is had a characteristic that
1, a variety of key factors of comprehensive analyzing influence power distribution network controllability complete intelligent distribution network controllability evaluation index
The building of system, so that evaluation index system is more scientific and comprehensive；
2, in view of the controllability ability for being difficult to direct solution and going out power distribution network, the present invention is innovative to be proposed to pass through scoring functions
(SF, Score Function) obtains the score of evaluation index, is fully considering influence of each key factor to intelligent distribution network
After mode and influence degree, the score function of index of correlation is established；
3, the assignment that weight is completed using analytic hierarchy process (AHP), improves the reasonability and objectivity of evaluation index system；
4, distributed generation resource is carried out using dynamic time warping (DTW, Dynamic Time Warping) method controllable
Property comprehensive assessment, controllability grade assessment is carried out by analyzing the similarity of index to be assessed and standard index, finally to intelligence
The controllability of energy power distribution network carries out comprehensive assessment.
Detailed description of the invention
Fig. 1 is flow chart of the invention.
Fig. 2 is analogue system schematic diagram of the invention.
Specific embodiment
For the expression for being more clear technical solution of the present invention, purpose and meaning, below by attached drawing and phase
The case study on implementation answered carries out the present invention to go deep into detailed description.The implementation case is only used for intuitively illustrating the present invention, not
The case where being only limitted to present case.
A kind of controllability dynamic time warping of intelligent distribution network proposed by the invention is associated with appraisal procedure, and process is as schemed
Shown in 1.
Case study on implementation
Intelligent distribution network controllability analogue system is established as shown in Fig. 2, being divided into 3 parts, is direct current distribution respectively
Power supply 1-k, DC energy storage power station (k+1)-h, load (h+1)-j.
Present case in order to acquire data diversity and procedure simulation it is succinct, choose distributed photovoltaic power, distribution
Fan power, micro-gas-turbine electromechanical source and energy-accumulating power station each one, rated capacity be respectively 40kVA, 100kVA, 70kVA,
60kVA.By adjusting the loading level of load, all data of distributed generation resource and energy-accumulating power station is acquired.
1) assessment data acquisition
According to the analogue system of foundation, and the power distribution network controllability evaluation index system for combining step 1 to determine, it can be according to formula
(1)~(4) distributed electrical source utilization rate index x is acquired1, power factor specification x2, variation index x3, finally obtain controllable
Property assessment needed for master sample index, reference sample index and sample index to be assessed.
This analogue system has carried out a large amount of emulation experiment in the case where fully taking into account loading level difference, for system
It makes scientific and reasonable reference sample and data support is provided, keep divided rank more scientific and reasonable, make the intelligent distribution network of description
Controllability more objective grade.
2) weight assignment of the building of master sample and index
Intelligent distribution network controllability criteria sample is the sample for making the controllability of intelligent distribution network reach optimum state.According to
Each index determines reference scale A to the influence degree of power distribution network1=[a11,a12,a13], A1Middle element is distributed generation resource respectively
Utilization rate index, power factor specification, variation index score function.Pass through commentary upper known to score function (5)~(8)
Divide all is 1.
The weight of each index is calculated using AHP weight assignment method, and it is normalized, and finally obtains weighting
Master sample vector.
Table 1 compares scale and its meaning
2 AHP judgment matrix of table
By the comparator matrix two-by-two in table 2 obtain matrix maximum eigenvalue and its corresponding feature vector, matrix
Maximum eigenvalue is 3, and corresponding feature vector is expressed as γ, the matrix be consistency matrix, random consistency ratio be 0 <
0.1, meet conformance requirement, the maximum feature vector γ of characteristic value is normalized, the vector of subjective weight is obtained
It is as follows:
γ=[0.7074 0.6119 0.3537]
The master sample vector for finally obtaining weighting is as follows:
A′1=[a '11 a′12 a′13]
=[0.4228 0.3658 0.2114]
3) division of the selection of reference sample and grade
By the analysis to intelligent power distribution Running State, chooses 3 groups of typical sample sequences in emulation data and be used as reference
It is as follows to ultimately form reference sample sequence for sequence:
Formula (9)~(11) in assessment algorithm are associated with by DTW, analytical calculation is carried out to reference sample, take its accumulation distance
The minimum bend distance in the matrix lower right corner is as association matching factor, the finally corresponding assessment of different grades of association matching factor
As a result as follows:
3 controllability evaluation grade of table divides
4) establishment of sample to be assessed
First against different load situation, the controllability subindex of distributed generation resource and energy storage device is measured respectively, and is utilized
Scoring functions score, and then form sample sequence to be assessed, wherein A2~A5For distributed generation resource under the first load condition
It scores with the evaluation index of energy-accumulating power station, A6~A9Assessment for distributed generation resource and energy-accumulating power station under second of load condition refers to
Mark scoring, A10~A13It scores, obtains immeasurable for the evaluation index of distributed generation resource and energy-accumulating power station under the third load condition
The scoring of guiding principle is as follows:
It reuses weight to be weighted scoring, it is as follows to obtain the nondimensional weighted scoring of sample to be assessed:
5) intelligent distribution network controllability comprehensive assessment
The association matching factor of sample to be assessed is calculated first with DTW association appraisal procedure, and forms each distribution
Association matching factor in the case of formula power supply different loads is as shown in table 4:
The association matching factor of distributed generation resource in the case of 4 different load of table
According to the association matching factor of Distributed Generation in Distribution System obtained above and energy-accumulating power station, in conjunction with influence intelligence
The key element of energy power distribution network controllability is it is found that the relative capacity of distributed generation resource and energy-accumulating power station has to pass weight controllability
The influence wanted, it follows that the controllability of intelligent distribution network is assessed.
It is comprehensive controllability can be carried out to the operating status of the intelligent distribution network in the case of three kinds of different loads according to formula (12)
Assessment.Assessment result is as shown in table 5:
5 intelligent distribution network controllability comprehensive assessment of table
To sum up, the present invention is analyzed for intelligent distribution network control ability, proposes intelligent distribution network controllability dynamic
The method of Time Warp association assessment.The critical index for influencing intelligent distribution network controllability is found out, controllability synthesis is formed and comments
Estimate system.Firstly, being scored using scoring functions index on the basis of combining Factors Affecting Parameters；Recycle index master
It sees weight to be weighted index, obtains reference sample and sample to be assessed；Then in intelligent distribution network controllability force estimation
Field proposes dynamic time warping association assessment, and sample to be assessed compared with master sample by obtaining accumulation distance square
Battle array obtains the association matching factor of distributed generation resource and energy-accumulating power station；Finally, the capacity in conjunction with above equipment obtains intelligent power distribution
The controllability comprehensive assessment ability of net.The comprehensive assessment index that the present invention constructs can be verified by emulation data and assessment result
System has extremely strong reasonability, and applicability with higher is assessed in the intelligent distribution network DTW association of proposition.
Claims (6)
1. a kind of controllability dynamic time warping of intelligent distribution network is associated with appraisal procedure, which comprises the following steps:
Step 1: the building of intelligent distribution network controllability evaluation index system；
Step 2: the scoring of assessment data acquisition and index；
Step 3: the weight assignment of evaluation index；
Step 4: the controllability DTW of intelligent distribution network is associated with assessment；
Step 5: the controllability DTW of intelligent distribution network is associated with assessment.
2. a kind of controllability dynamic time warping of intelligent distribution network according to claim 1 is associated with appraisal procedure, special
Sign is, the step 1 specifically:
Step 1-1: inclined in the real-time power output, the state-of-charge of energy-accumulating power station, power factor, voltage for fully considering distributed generation resource
After these influence factors are moved to the influence mode and influence degree of intelligent distribution network controllability, intelligent distribution network controllability is formed
Evaluation index system, including distributed electrical source utilization rate index, energy-accumulating power station state-of-charge index, power factor specification and voltage
Offset target；
Step 1-2: according to intelligent distribution network controllability evaluation index system, master sample sequence is established, setting master sample is X1
=[x11,x12,x13], it respectively corresponds and contributes in real time for distributed generation resource: distributed electrical source utilization rate or the charged shape of energy-accumulating power station
State；Control ability that distributed generation resource is idle: power factor；Voltage regulation capability: variation, index calculation such as following formula:
Distributed electrical source utilization rate index:
Energy-accumulating power station state-of-charge index:
Power factor specification:
Variation index: Δ Ui=| 1-Ui|
In above formula, PDG,iThe active power that distributed generation resource or energy-accumulating power station issue, QDG,iDistributed generation resource or energy-accumulating power station absorb
Or the reactive power issued, SN,iThe rated capacity of distributed generation resource or energy storage power station grid connection inverter, EC,iEnergy-accumulating power station remains
Covolume amount, UiGrid entry point standard voltage value；
Step 1-3: master sample baseline impact scale sequence A is established1=[a11,a12,a13], while A1As final assessment sample
The first row of this matrix A；a11For the utilization rate index of distributed generation resource, a12For power factor specification, a13Refer to for variation
Mark.
3. a kind of controllability dynamic time warping of intelligent distribution network according to claim 1 is associated with appraisal procedure, special
Sign is, the step 2 specifically:
Step 2-1: the master sample sequence middle finger target calculation according to step 1 acquires intelligent distribution network controllability
Data needed for assessing form reference data sample sequence and data sample sequence to be assessed；It can by score function master sample
Obtaining master sample scoring is 1, and each index score function is shown below:
Distributed electrical source utilization rate score function: ai10≤η≤1=1- η
Energy-accumulating power station state-of-charge score function:
Power factor score function:
Variation score function:
Step 2-2: forming each evaluation index by the data acquired, and establish score function according to the influence factor of each index, benefit
It is scored with score function to reference sample and sample to be assessed.
4. a kind of controllability dynamic time warping of intelligent distribution network according to claim 1 is associated with appraisal procedure, special
Sign is, the step 3 specifically:
Distributed electrical source utilization rate index, power factor in evaluation index system can be referred to using the index weights assignment method of AHP
Mark, variation index carry out subjective assignment；
Step 3-1: according to each evaluation index to the influence degree of intelligent distribution network controllability, it is compared to each other the weight for obtaining each index
The property wanted degree chooses the size for comparing scale, and then forms multilevel iudge matrix；
Step 3-2: by comparator matrix two-by-two obtain matrix maximum eigenvalue and its corresponding feature vector, complete consistency
Verification is chosen again if being unsatisfactory for consistency desired result and compares scale；
Step 3-3: to the judgment matrix for meeting above-mentioned condition, returned using maximum eigenvalue and its feature vector implementation sought
Subjective weight assignment is completed in one change processing；Master sample distance sequence, reference sample using subjective weight, after finding out weighting
Distance sequence and sample distance sequence to be assessed.
5. a kind of controllability dynamic time warping of intelligent distribution network according to claim 1 is associated with appraisal procedure, special
Sign is, the step 4 specifically:
By calculate solve two groups of sample sequences minimum accumulated distance, recycle minimum accumulated distance come measure two samples it
Between similarity degree；
Step 4-1: calculate distance matrix: using following formula calculation formula can obtain corresponding element in two sample sequences it is European away from
From λij,
In formula, u and v respectively indicate two sample sequences for needing to compare, and corresponding element can use i=2,3 ..., m and j=2,
3,…,n；Euclidean distance is arranged according to certain rules can be obtained distance matrix and is shown below:
Step 4-2: calculate accumulation distance matrix: calculation method is shown below, and obtains minimum bend by accumulation distance matrix
Distance i.e. association matching factor；D (i, j) indicates the minimum bend distance that (i, j) is arrived from (1,1), the value of D (m, n) i.e. two sample
The minimum bend distance of this sequence, reflects the similarity degree of two samples；
Step 4-3: by reference to the association matching factor C of sample sequenceiTo determine the range of different controllability grades；And it will be to
The association matching factor of sample sequence and master sample sequence is assessed compared with above range, finally obtain sample to be assessed can
Control property grade.
6. a kind of controllability dynamic time warping of intelligent distribution network according to claim 1 is associated with appraisal procedure, special
Sign is, the step 5 specifically:
Using DTW association appraisal procedure the association matching factor of sample to be assessed is calculated, and formed each distributed generation resource and
Association matching factor in the case of energy-accumulating power station different loads；According to Distributed Generation in Distribution System obtained above and energy storage electricity
The association matching factor stood, in conjunction with the key element for influencing intelligent distribution network controllability it is found that distributed generation resource and energy storage electricity
The relative capacity stood has vital influence to controllability, it follows that the controllability of intelligent distribution network is assessed；
Calculation formula is shown below:
In formula, n is the number of distributed generation resource and energy-accumulating power station in intelligent distribution network, STFor distributed generation resource and energy-accumulating power station
Total capacity, SiFor distributed generation resource or the capacity of energy-accumulating power station, CiTo be associated with matching factor accordingly.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110991896A (en) * | 2019-12-04 | 2020-04-10 | 南京理工大学 | Point-area-network multi-granularity evaluation method for voltage running state of active power distribution network |
| CN111144703A (en) * | 2019-12-04 | 2020-05-12 | 南京理工大学 | Power distribution network partition voltage running state evaluation method based on fuzzy dynamic time warping |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103715686A (en) * | 2014-01-08 | 2014-04-09 | 国家电网公司 | Energy efficiency analysis method suitable for direct-current power distribution network circuits |
| CN106339801A (en) * | 2016-08-23 | 2017-01-18 | 江苏方天电力技术有限公司 | Photovoltaic power station reactive power control capability evaluation method |
| EP3238313A1 (en) * | 2014-12-22 | 2017-11-01 | Robert Bosch GmbH | Method for adaptive demand charge reduction |
-
2018
- 2018-06-13 CN CN201810607425.7A patent/CN109063950B/en active Active
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103715686A (en) * | 2014-01-08 | 2014-04-09 | 国家电网公司 | Energy efficiency analysis method suitable for direct-current power distribution network circuits |
| EP3238313A1 (en) * | 2014-12-22 | 2017-11-01 | Robert Bosch GmbH | Method for adaptive demand charge reduction |
| CN106339801A (en) * | 2016-08-23 | 2017-01-18 | 江苏方天电力技术有限公司 | Photovoltaic power station reactive power control capability evaluation method |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110991896A (en) * | 2019-12-04 | 2020-04-10 | 南京理工大学 | Point-area-network multi-granularity evaluation method for voltage running state of active power distribution network |
| CN111144703A (en) * | 2019-12-04 | 2020-05-12 | 南京理工大学 | Power distribution network partition voltage running state evaluation method based on fuzzy dynamic time warping |
| CN110991896B (en) * | 2019-12-04 | 2022-08-12 | 南京理工大学 | Point-area-network multi-granularity evaluation method for voltage running state of active power distribution network |
| CN111144703B (en) * | 2019-12-04 | 2022-09-27 | 南京理工大学 | Power distribution network partition voltage running state evaluation method based on fuzzy dynamic time warping |
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Application publication date: 20181221 Assignee: Nanjing Qianyuan Electric Power Technology Co.,Ltd. Assignor: NANJING University OF SCIENCE AND TECHNOLOGY Contract record no.: X2022980027425 Denomination of invention: A Dynamic Time Bending Correlation Evaluation Method for Controllability of Intelligent Distribution Network Granted publication date: 20220315 License type: Exclusive License Record date: 20221229 |
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