CN107679687A - A kind of photovoltaic output modeling method and Generation System Reliability appraisal procedure - Google Patents
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Abstract
The present invention relates to a kind of photovoltaic output modeling method, including：1）The year sequential of sample is contributed using Fisher optimal segmentations algorithm according to effective output photovoltaic day, length time and carries out optimal segmentation, forms the data set of day part；2）Fuzzy c-Means Clustering Algorithm model is built, and cluster analysis is carried out one by one to the day part data set using the Fuzzy c-Means Clustering Algorithm model, until the Euclidean distance of data set and corresponding cluster centre is minimum.Have the beneficial effect that：Using Fisher optimal segmentations method to the piecewise fine modeling of photovoltaic output sequence, the local sequential feature of this area's photovoltaic power can be more embodied, there is stronger practicality and specific aim；Using FCM multidimensional clustering algorithms, cluster analysis is carried out to day part photovoltaic power and workload demand, this method simple and highly efficient the characteristics of simulating the randomness and timing that stochastic variable has.
Description
Technical field
The present invention relates to the grid-connected reliability consideration of renewable energy power, more particularly to a kind of photovoltaic output modeling method with
And Generation System Reliability appraisal procedure.
Background technology
With the rapid development of economy, electricity needs is continuously increased, and the large-scale application of regenerative resource meets society
Requirement to environmental protection, energy-saving and emission-reduction and sustainable development.After rational planning, they can postpone transmission ＆ distribution
The construction or upgrading of electric network, reduce network outages and strengthening system safety in operation and reliability, improve system electricity
Energy quality etc. produces beneficial effect.Wherein, photovoltaic generation is quickly grown in recent years, system of the accurate evaluation containing photovoltaic generation
Reliability becomes particularly significant, has research to predict, 2 000MWp are up to China's Photovoltaic generation installed capacity in 2020, counts
Draw and increase by more than 15% in year.
In the reliability consideration containing photovoltaic generating system, the modeling that photovoltaic is contributed is the focus studied instantly.At present, state
The inside and outside research for going out force modeling to photovoltaic can be divided into two classes：One kind is the physical modeling based on solar energy resources.Such
In model, based on analysis irradiation intensity, the factor such as temperature and photovoltaic array angle, by photoelectric conversion process, photovoltaic is finally given
The power output of system.The data volume that its modeling process needs is big, calculates more complicated；Another kind of is to be contributed with photovoltaic history as base
The statistical modeling of plinth, directly by the statistical analysis to photovoltaic plant history power output, utilize Monte-Carlo step technology mould
Photovoltaic plant power output is drawn up, this method enormously simplify opto-electronic conversion model.Document one《Photovoltaic based on Markov chain
Electricity generation system power output short term prediction method》(electric power network technique, 2011, volume 35, the 1st phase, page 152 to page 157) adopt
Statistical modeling, document two have been carried out with being contributed based on the clustering technique of Markov Process as Applied to photovoltaic generation《Based on neutral net
Photovoltaic array generating forecast model design》(electrotechnics journal, 2009, volume 24, the 9th phase, page 153 to 158
Page) use the clustering technique of neutral net, above method is relatively cumbersome.Document three《A time-dependent
approach to evaluate capacity value of wind and solar PV generation》(IEEE
Transactions on Sustainable Energy, 2016, volume 7, the 1st phase, page 129 to page 138) in consider
The characteristic and correlation diurnal periodicity that photovoltaic is contributed and load has, using a kind of technology of cluster, analyzes photovoltaic generating system
Confidence capacity.But the reliability index of the use of document three can only reflect the average level of annual time scale, it is impossible to accurate to carve
Influence of the day part photovoltaic to electricity generation system in drawing 1 year, its reliability index are excessively coarse, it is impossible to reflect that photovoltaic is contributed season
Characteristic.
In to the system Reliability Research containing photovoltaic plant, generally directed to be a year and a day photovoltaic and load data,
The result of calculating can only also characterize comprehensive contribution of the photovoltaic generation to system whole year abundant intensity, the application of the reliability assessment
It is narrower, it is limited to actual production directive function.But inherently differed for different regions, its photovoltaic power producing characteristics.Only
From the time scale of whole year, it is difficult to do the research to become more meticulous to influence of the photovoltaic generation to system reliability.It is therefore necessary to grind
Various Seasonal and in a few days influence of the different periods photovoltaic generation to system reliability are studied carefully, to reach in shorter time dimension
On, the influence of finer consideration photovoltaic resources characteristic and part throttle characteristics to system reliability.And the most frequently used segmentation side
Method is the dividing mode according to season, i.e., annual time scale is divided into 4 periods, corresponded to respectively：Spring, summer, autumn and winter.But should
Method is a kind of fuzzy, segmentation for being manually set, without the foundation of reality, it is impossible to for somewhere actual photovoltaic contribute it is special
Property carry out that there is targetedly optimal segmentation.
The content of the invention
Present invention aims to overcome that the deficiency of above-mentioned prior art, there is provided a kind of photovoltaic output modeling method and hair
Electric system reliability estimation method, specifically there is following technical scheme realization：
The photovoltaic output modeling method, including：
The year sequential of sample is gone out using Fisher optimal segmentations algorithm according to effective output photovoltaic day, length time
Power carries out optimal segmentation, forms the data set of day part；
Fuzzy c-Means Clustering Algorithm model is built, and using the Fuzzy c-Means Clustering Algorithm model to the day part
Data set carries out cluster analysis one by one, carries out building object function first during cluster analysis, then straight to object function iteration optimizing
It is minimum to the Euclidean distance of data set and corresponding cluster centre.
The further design of the photovoltaic output modeling method is, the structure of the Fisher optimal segmentations algorithm model
Including：
Set { X1,X2,…,XnIt is n ordered sample, each sample is m dimensional vectors, and the sample is divided, record
A certain section of sample be：
G (i, j)={ Xi,Xi+1,…,Xj} (1)
Using description of the sum of squares of deviations as this section of diameter, i.e.,：
In formula, D (i, j) is the ordered sample from i-th of sample to the sum of squares of deviations of j-th of sample；For the section
The average of ordered sample；
The ordered sample is divided into k sections, every section of sample index is designated as Bj={ ij,ij+1,…,ij+1- 1 }, j ∈ 1,
2 ..., k }, quantile therein meets：1=i1＜ i2＜ ... ＜ ik＜ n=ik+1, total object function is obtained, such as formula (4)：
In formula, L is each section of deviation total sum of squares, and L values are smaller, and segmentation is more reasonable.
The further design of the photovoltaic output modeling method is, the target of the Fuzzy c-Means Clustering Algorithm model
Function such as formula (5)：
In formula, U is subordinated-degree matrix；C is cluster centre matrix；M is weighting multiple；dijFor ith cluster center and jth
Euclidean distance between individual data point.
3rd, photovoltaic output modeling method according to claim 1, it is characterised in that the Fuzzy c-Means Clustering Algorithm
For iteration searching process, cluster centre battle array and degree of membership battle array are updated by formula (7), formula (8)：
If front and rear iterative process twice, the knots modification of object function is less than some threshold value, then cluster process terminates：
||J(U(z+1), C(z+1))-J(U(z), C(z)) | | ＜ 9 (9)
In formula：J(U(z),C(z)) for the target function value of the z times iteration, threshold epsilon typically take 10-4。
A kind of Generation System Reliability appraisal procedure is provided according to the photovoltaic output modeling method, based on optimal segmentation
It is as follows with multidimensional clustering algorithm, step：
Step 1) recombinates to photovoltaic output sequence, forms with the data mode of arrangement in 24 hours one day, forms matrix
Form is the photovoltaic output battle array P of 365 row * 24 rowpv；
Step 2) statistics obtains photovoltaic effective output time series Tpv, according to the original of the daily effective output time length of photovoltaic
Then, using Fisher optimal segmentation algorithms, force data progress sequential segmentation is gone out to the photovoltaic history of year simulation cycle, obtained optimal
Waypoint；
Step 3) is in each period, respectively to photovoltaic power and workload demand data, when determining each by FCM clustering procedures
The cluster centre and fuzzy membership matrix of section photovoltaic power, the cluster centre and fuzzy membership matrix of day part load；
Step 4) is simulated to the running status of the photovoltaic power of each period, workload demand and conventional power unit, system
The reliability index of meter systems.
The further design of the Generation System Reliability appraisal procedure is that the step 4) passes through Monte Carlo state
The methods of sampling is, it is specified that frequency in sampling is 105It is secondary.
The further design of the Generation System Reliability appraisal procedure is, expected energy not supplied is used in step 4)
LOEE is as reliability index, LOEE expression formula such as formula (10)：
In formula：S is the iterations in sampled analog；T is moment point, h；N is the iteration total degree of setting；TdayFor this
The number of days of period；G is the quantity of whole conventional power units；Ds,tAnd Ps,tIn respectively the s times iteration, needed in moment t load
The amount of asking and photovoltaic power.
Beneficial effects of the present invention：
1st, photovoltaic output modeling method, it is characterised in that including：
According to effective output photovoltaic day, length time using Fisher optimal segmentations algorithm the year sequential of sample is contributed into
Row optimal segmentation, form the data set of day part；
Fuzzy c-Means Clustering Algorithm model is built, and using the Fuzzy c-Means Clustering Algorithm model to the day part
Data set carries out cluster analysis one by one, until the Euclidean distance of data set and corresponding cluster centre is minimum.
Embodiment
The present invention program is described in detail below.
The photovoltaic output modeling method of the present embodiment, including two steps are respectively：1) when according to photovoltaic day effective output
Between length the year sequential of sample contributed using Fisher optimal segmentations algorithm carry out optimal segmentation, form the data of day part
Collection.2) Fuzzy c-Means Clustering Algorithm model is built, and using the Fuzzy c-Means Clustering Algorithm model to the day part number
Cluster analysis is carried out one by one according to collection, until the Euclidean distance of data set and corresponding cluster centre is minimum.Fisher optimal segmentations are calculated
Method model：
Assuming that { X1,X2,…,XnIt is n ordered sample, each sample is m dimensional vectors.The sample is divided, recorded
A certain section of sample be：
G (i, j)={ Xi,Xi+1,…,Xj} (1)
Using description of the sum of squares of deviations as this section of diameter, i.e.,：
In formula：D (i, j) is the ordered sample from i-th of sample to the sum of squares of deviations of j-th of sample；For the section
The average of ordered sample.
When having obtained every section of sum of squares of deviations, if the ordered sample is divided into k sections, every section of sample index is designated as Bj
={ ij,ij+1,…,ij+1- 1 }, j ∈ { 1,2 ..., k }, quantile therein meet：1=i1＜ i2＜ ... ＜ ik＜ n=ik+1。
So as to obtain total object function, as shown in formula (4).
In formula：L is each section of deviation total sum of squares, and L values are smaller, and segmentation is more reasonable.
There are some researches show linear relation is presented in sunshine-duration of the illumination irradiation level of, given area often with this area.
I.e. in certain time period, sunshine-duration of one day grow section substantially reflect irradiation level power.And for photovoltaic generating system, light
Volt is contributed directly to be influenceed by irradiation level again, so the length of sunshine-duration embodies the power of photovoltaic output indirectly.Based on this,
The present invention discloses a kind of new segmented mode, i.e., according to the principle of photovoltaic effective output time length in one day, photovoltaic year is gone out
Power carries out ordered section.
Fuzzy c-Means Clustering Algorithm model：
The target of the algorithm is so that the Euclidean distance of data set and corresponding cluster centre is minimum, and object function is as follows：
In formula：U is subordinated-degree matrix；C is cluster centre matrix；M is weighting multiple；dijFor ith cluster center and jth
Euclidean distance between individual data point.
The algorithm is an iteration searching process, cluster centre battle array and degree of membership battle array can be carried out by following two formula
Renewal.
If front and rear iterative process twice, the knots modification of object function is less than some threshold value, then cluster process terminates：
||J(U(z+1), C(z+1))-J(U(z), C(z)) | | ＜ ε (9)
In formula：J(U(z),C(z)) for the target function value of the z times iteration, threshold epsilon typically take 10-4。
The present invention is used as reliability index using expected energy not supplied (loss of energy expection, LOEE),
The index not only preferably reflects the size of system short of electricity amount, the system reliability that can be more reflected in each period.
In formula：S is the iterations in sampled analog；T is moment point, h；N is the iteration total degree of setting； TdayFor this
The number of days of period；G is the quantity of whole conventional power units；Ds,tAnd Ps,tIn respectively the s times iteration, needed in moment t load
The amount of asking and photovoltaic power.
The present embodiment is according to the method for above-mentioned photovoltaic output Series Modeling, there is provided one kind is based on optimal segmentation and multidimensional clustering
Reliability Modeling.This method is contributed to photovoltaic carry out sequential segment processing first；Then cluster analysis is carried out to every section,
Sampled analog obtains the reliability index value of system.Specific calculation procedure is as follows：
Step 1) recombinates to photovoltaic output sequence, forms with the data mode of arrangement in 24 hours one day, forms matrix
Form is the photovoltaic output battle array P of 365 row * 24 rowpv。
Step 2) statistics obtains photovoltaic effective output time series Tpv, according to the original of the daily effective output time length of photovoltaic
Then, using Fisher optimal segmentation algorithms, force data progress sequential segmentation is gone out to the photovoltaic history of year simulation cycle, obtained optimal
Waypoint.
Step 3) is in each period, respectively to photovoltaic power and workload demand data, when determining each using FCM clustering procedures
Between section cluster numbers, cluster centre and fuzzy membership battle array.It should be noted that cluster analysis and the photovoltaic power of workload demand
Analysis method is identical, repeats no more here.
In summary 3 steps obtain step 4)：The cluster centre and fuzzy membership matrix of each period photovoltaic power, respectively
The cluster centre and fuzzy membership matrix of individual period load, the capacity and fault rate of the conventional power unit of RTS test systems.Utilize
Monte Carlo state sampling technology is, it is specified that frequency in sampling is 105It is secondary, to the photovoltaic power of each period, workload demand and often
The running status of rule unit is simulated, the reliability index of statistical system.
Compared with prior art, the advantages of present invention is prominent includes：First, in reliability assessment containing photovoltaic generating system
The date periodicity round the clock and season timing cycles of photovoltaic output are considered, photovoltaic is contributed using Fisher optimal segmentations method
The piecewise fine modeling of sequence, the local sequential feature of this area's photovoltaic power can be more embodied, there is stronger practicality and be directed to
Property；Secondly, using FCM multidimensional clustering algorithms, cluster analysis is carried out to day part photovoltaic power and workload demand, this method is simple
And the characteristics of efficiently simulating the randomness and timing that stochastic variable has；Finally, with reference to Monte Carlo state sampling side
Method to carrying out fail-safe analysis containing photovoltaic generating system, institute's extracting method can effective lifting system reliability assessment precision, quantization
After analysis access photovoltaic plant, system is in the situation of change of different time sections reliability, the grid connection capacity planning to photovoltaic plant
With great importance.
Photovoltaic output modeling method provided by the invention and Generation System Reliability appraisal procedure have been carried out in detail above
It is thin to introduce, in order to understand the present invention and its core concept., in the specific implementation, can for those of ordinary skill in the art
A variety of modifications and deduction are carried out according to the core concept of the present invention.In summary, this specification is not construed as the limit to the present invention
System.
Claims (7)
- A kind of 1. photovoltaic output modeling method, it is characterised in that including：The year sequential of sample is contributed using Fisher optimal segmentations algorithm according to effective output photovoltaic day, length time and carried out most Optimal sorting section, form the data set of day part；Fuzzy c-Means Clustering Algorithm model is built, and using the Fuzzy c-Means Clustering Algorithm model to the day part data Collection carries out cluster analysis one by one, carries out building object function during cluster analysis first, then to the optimizing of object function iteration until number Euclidean distance according to collection and corresponding cluster centre is minimum.
- 2. photovoltaic output modeling method according to claim 1, it is characterised in that the Fisher optimal segmentations algorithm mould The structure of type includes：Set { X1,X2,…,XnIt is n ordered sample, each sample is m dimensional vectors, and the sample is divided, and records sample A certain section be：G (i, j)={ Xi,Xi+1,…,Xj} (1)Using description of the sum of squares of deviations as this section of diameter, i.e.,：In formula, D (i, j) is the ordered sample from i-th of sample to the sum of squares of deviations of j-th of sample；It is orderly for the section The average of sample；The ordered sample is divided into k sections, every section of sample index is designated as Bj={ ij,ij+1,…,ij+1- 1 }, j ∈ 1,2 ..., K }, quantile therein meets：1=i1＜ i2＜ ... ＜ ik＜ n=ik+1, total object function is obtained, such as formula (4)：In formula, L is each section of deviation total sum of squares, and L values are smaller, and segmentation is more reasonable.
- 3. photovoltaic output modeling method according to claim 1, it is characterised in that the Fuzzy c-Means Clustering Algorithm model Object function such as formula (5)：In formula：U is subordinated-degree matrix；C is cluster centre matrix；M is weighting multiple；dijFor ith cluster center and j-th of number Euclidean distance between strong point, μijFor j-th of data point and the degree of membership at ith cluster center.
- 4. photovoltaic output modeling method according to claim 1, it is characterised in that the Fuzzy c-Means Clustering Algorithm is repeatedly For searching process, cluster centre battle array and degree of membership battle array are updated by formula (7), formula (8)：If front and rear iterative process twice, the knots modification of object function is less than some threshold value and (is generally less than 10-3), then cluster process knot Beam：||J(U(z+1),C(z+1))-J(U(z),C(z)) | | ＜ ε (9)In formula：J(U(z),C(z)) for the target function value of the z times iteration.
- 5. the Generation System Reliability appraisal procedure of the photovoltaic output modeling method as described in claim any one of 1-4, it is special Sign is as follows based on optimal segmentation and multidimensional clustering algorithm, step：Step 1) recombinates to photovoltaic output sequence, forms with the data mode of arrangement in 24 hours one day, forms matrix form For the photovoltaic output battle array P of 365 row * 24 rowpv；Step 2) statistics obtains photovoltaic effective output time series Tpv, according to the principle of the daily effective output time length of photovoltaic, Using Fisher optimal segmentation algorithms, force data progress sequential segmentation is gone out to the photovoltaic history of year simulation cycle, obtains most optimal sorting Duan Dian；Respectively to photovoltaic power and workload demand data, day part light is determined by FCM clustering procedures in each period for step 3) Lie prostrate the cluster centre and fuzzy membership matrix of power, the cluster centre and fuzzy membership matrix of day part load；Step 4) is simulated to the running status of the photovoltaic power of each period, workload demand and conventional power unit, department of statistic The reliability index of system.
- 6. Generation System Reliability appraisal procedure according to claim 5, it is characterised in that the step 4) is special by covering Caro state sampling method is, it is specified that frequency in sampling is 105It is secondary.
- 7. Generation System Reliability appraisal procedure according to claim 5, it is characterised in that in step 4) using electricity not Foot it is expected LOEE as reliability index, LOEE expression formula such as formula (10)：In formula：S is the iterations in sampled analog；T is moment point, h；N is the iteration total degree of setting；TdayFor the time The number of days of section；G is the quantity of whole conventional power units；Ds,tAnd Ps,tIn respectively the s times iteration, in moment t workload demand amount And photovoltaic power.
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| CN114896871A (en) * | 2022-04-22 | 2022-08-12 | 国网江苏省电力有限公司电力科学研究院 | Photovoltaic output decomposition method based on minimum mutual information |
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