CN110336332A - A kind of Interval Power Flow typical scene building method based on power curve polymerization - Google Patents
A kind of Interval Power Flow typical scene building method based on power curve polymerization Download PDFInfo
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- H02J3/382—
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J3/00—Circuit arrangements for ac mains or ac distribution networks
- H02J3/38—Arrangements for parallely feeding a single network by two or more generators, converters or transformers
- H02J3/46—Controlling of the sharing of output between the generators, converters, or transformers
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- H—ELECTRICITY
- H02—GENERATION; CONVERSION OR DISTRIBUTION OF ELECTRIC POWER
- H02J—CIRCUIT ARRANGEMENTS OR SYSTEMS FOR SUPPLYING OR DISTRIBUTING ELECTRIC POWER; SYSTEMS FOR STORING ELECTRIC ENERGY
- H02J2203/00—Indexing scheme relating to details of circuit arrangements for AC mains or AC distribution networks
- H02J2203/20—Simulating, e g planning, reliability check, modelling or computer assisted design [CAD]
Abstract
The present invention relates to a kind of Interval Power Flow typical scene building method based on power curve polymerization, step S1: wind speed, intensity of illumination data are updated to scene power output formula, obtain RDG sunrise force curve sample；Step S2: from a curve is randomly selected in sample as first curve in initial center；Step S3: construction initial center；Step S4: residual curve is calculated to the Euclidean distance of K cluster centre, residual curve is divided into corresponding cluster classification, K class collection of curves is generated；Step S5: K cluster centre curve is updated；Step S6: judge whether to reach the condition of convergence；If it is executing step S7, otherwise return step S4；Step S7: being clustered using different K values, is calculated the profile parameters of corresponding result, is selected optimum cluster K value；Step S8: Interval Power Flow typical scene is generated；Step S9: it is contributed interval computation Interval Power Flow according to 24 × K group hour.The present invention can be avoided the section ultra-wide degree problem in bulk sample this spatial sampling computation interval trend.
Description
Technical field
The present invention relates to new energy field, especially a kind of Interval Power Flow typical scene construction based on power curve polymerization
Method.
Background technique
To cope with increasingly serious global energy crisis and environmental problem, extensive, high permeability distributed type renewable energy
Source (Renewable Distributed Generation, RDG) is grid-connected to have become inexorable trend.Wind, the light distributed energy
It is influenced by factors such as geographical location, natural environment, weather conditions, power producing characteristics often have strong randomness and fluctuation.
Using existing certainty tidal current computing method consider uncertainty there are biggish difficulty, result also tend to
Subsequent practical operation situation difference is larger.
It is calculated based on Interval Power Flow, and establishing range optimization model is a kind of effective uncertainty optimization Planning instrument,
But before this in order to seek globally optimal solution, it has to the computation interval trend on total state space, so that Interval Power Flow calculated
Conservative tremendous expansion, calculated result lose engineering application value.
It is presently considered there are mainly three types of uncertain most common methods: one is being contributed probabilistic model based on new energy,
Monte Carlo simulation is embedded in by Probabilistic Load Flow and carries out multiple-objection optimization, one is based on new energy power output section, passes through calculating
Interval Power Flow carries out range optimization, and there are also one is convert certainty for uncertain problem based on a variety of typical Run-time scenarios
Problem.The probabilistic model that first method needs to obtain power supply power output calculates Probabilistic Load Flow, and there are data acquisition difficulty greatly, probability
The problems such as parameter is inaccurate, computationally intensive, limits the application of this method.Second method carries out trend in the form of interval number
It calculates, Interval Power Flow can cover all uncertain situations, but there are certain Conservative Properties.The third method construct allusion quotation
Type scene, uncertain Load flow calculation are disassembled as multiple certainty Load flow calculations, how to select representative scene to guarantee
It is the difficult point of this method all the time that all uncertain situations, which can be covered,.Current method is considering uncertain problem meter
It is difficult to guarantee model computation complexity and computational accuracy simultaneously when calculating system load flow.
Summary of the invention
In view of this, the purpose of the present invention is to propose to a kind of Interval Power Flow typical scene constructions based on power curve polymerization
Method can be avoided the section ultra-wide degree problem in bulk sample this spatial sampling computation interval trend.
The present invention is realized using following scheme: a kind of Interval Power Flow typical scene construction side based on power curve polymerization
Method, comprising the following steps:
Step S1: enabling one period have L days, provides wind speed, the intensity of illumination data in this period, and by the data generation
Enter into scene power output formula and calculated, obtains L wind, the light day power curve in period；
Step S2: the L wind, light day power curve are expressed as Ni={ ψ (1), ψ (2) ..., ψ (L) }, every curve
All it is a n-dimensional vector, includes that wind-powered electricity generation, the photovoltaic at 24 moment goes out force data；Using L wind, light day power curve as original
Beginning sample set Ni, clusters number K is set, at random from NiOne curve of middle selectionAs initial center T(0)In first song
Line；
Step S3: according to formula (1) calculated in remaining sample each curve withEuclidean distanceChoose d
Maximum curve is as Article 2 initial center curveInitial center at this time
In formulaIndicate the distance between curve, ψi(k) the kth dimension data for being curve i,Indicate cluster centre
J-th strip curve；
For remaining sample set Mi(Mi∈Ni/T(0)) every curve is calculated to T(0)The distance of middle curve, takes sum of the distance
Maximum curve is next initial center curve；The calculating for executing K maximum distance, obtains K initial cluster center curve
Step S4: original sample collection N is calculatediThe middle residual curve for removing cluster centre curve is to K cluster centre curveEuclidean distance, the nearest curve of distance in each curve and cluster centre is classified as a kind of scene, by
This obtains K collection of curves, and each collection of curves is known as a scene；
Step S5: the average value of every power curve synchronization data in K scene is calculated, new cluster centre is obtained
Curve updates K cluster centre curve；
Step S6: when K cluster centre curve no longer changes, then it is assumed that clustering convergence, L curve sample are divided into K
Class collection of curves, if in each collection of curves including stem curve；Judge whether to reach the condition of convergence；If it is thening follow the steps
S7, otherwise return step S4；
Step S7: cluster sample is made of L wind, light day power curve, and clusters number K value is rangeInterior
Integer executes step S2 to step S6 using different clusters number K, calculates total profile parameters of result after different K values cluster, than
More total profile parameters size selects optimal K value, and executing the K scene that step S2 to S6 is obtained according to the K value is cluster result；
Step S8: according to RDG daily output curve data construction 24 × K group hour power output section in each scene, section is generated
Trend typical scene；
Step S9: it is contributed interval computation Interval Power Flow according to 24 × K group hour that step S8 is obtained.
Further, the particular content of the step S1 are as follows:
Wind speed, the intensity of illumination data v in one period are providedi,t、hi,t, wherein i=1,2,3 ..., L, L are this period
Number of days, 0 < L < 3650, t indicate 24 hours；The data are updated in formula (2) and formula (3) and are calculated.
P in formulawi,tFor the output power of i-th day t-th moment wind-power electricity generation, vi,tIndicate the wind at i-th day t-th moment
Speed, vs、vrAnd v0Respectively indicate rated wind speed, incision wind speed and cut-out wind speed；
P in formulavi,tFor the output power of i-th day t-th moment photovoltaic power generation, hi,tIndicate the reality at i-th day t-th moment
Border intensity of illumination, hrIndicate specified intensity of illumination, PVRFor rated output power；
I-th day wind-powered electricity generation daily output time series data P is calculatedW(i)=(Pwi,1,Pwi,2,…,Pwi,24) and photovoltaic daily output
Time series data PV(i)=(Pvi,1,Pvi,2,…,Pvi,24), merge into wind, the light power curve ψ (i)=[P on the same daywi,1,
Pwi,2,…,Pwi,24,Pvi,1,Pvi,2,…,Pvi,24], obtain L days sunrise force curves { ψ (1), ψ (2) ..., ψ (L) }.
Further, the step S7 specifically includes the following contents:
Step S71: cluster sample is made of L wind, light day power curve, and clusters number K value is rangeInterior
Integer executes step S2 to S6 to sample curve using different K values, obtains corresponding to K cluster result；
Step S72: the cluster result after clustering for every kind of K value passes through profile parameters S (ψi) quantization Clustering Effect, wheel
Wide parameter S (ψi) value range be [- 1,1]；
A (ψ in formulai) it is cluster condensation degree, indicate the Euclidean distance mean value of other curves in curve and similar scene；b(ψi)
For clustering separation, the Euclidean distance mean value of all curves in curve and other scenes is indicated；
Total profile parameters StIs defined as:
Step S73: compare total profile parameters S that calculating formula (4) and formula (5) obtain under different K values cluster resulttSize,
The maximum cluster result Clustering Effect of total profile parameters is optimal, and corresponding K value is optimum cluster K value, executes step according to the K value
The K scene that S2 to S6 is obtained is cluster result.
Further, the step S8 specifically includes the following contents:
Enabling has s RDG sunrise force curve in k-th of scene, as shown in formula (6), the power output sequence of t moment in the scene
Pw,t={ Pwr,t,Pwo,t,...,Pws,t}；By sequence Pw,tGo out that force data is ascending is rearranged for new sequence Y={ y1,
y2,...,ys, sequence Y is handled according to formula (7), by yiWith its intermediate value ziInstead of obtaining sequence Z={ z1,z2,...,
zs}；Using data in sequence Z as foundation, new power output section [minZ, maxZ] is obtained；
Go out force data to 24 hours of the scene to handle, obtains 24 groups of hour RDG power output sections[P in formulardg,i] indicate that RDG is in the power output section at i-th of moment of the scene in scene；According to
Secondary to carry out interval structure to K scene, obtaining 24 × K group hour contributes section.
Further, the step S9 specifically includes the following steps:
Step S91: calculate node calculates power:
S in formulaiIndicate that node calculates power, SLiFor node injecting power, yi0For branch admittance over the ground；
Step S92: since distribution network end, being gradually pushed forward, and seeks each branch power S of power distribution network by node voltageijPoint
Cloth；
[S in formulaij] it is branch power, Δ SijFor line power loss, Pj、QjFor node active and reactive power, ZijFor line
Roadlock is anti-, SijFor branch power；
Step S93: node voltage section is asked by branch power
In formulaRespectively indicate the component in length and breadth of branch pressure drop；
Step S94: convergence criterion: iteration ends criterion is the voltage range [U of each nodei] bound is relative to the last time
The numerical bias of iteration is less than permissible value such as formula (15)；
In formulaThe respectively voltage magnitude upper and lower bound of kth time interior joint j, ε is deviation allowable value；
Voltage range [the U of each node is obtained after convergencei], i.e. Interval Power Flow calculated result.
Compared with prior art, the invention has the following beneficial effects: proposition is clustered using RDG power curve as sample,
Constructing hour contributes section, and then obtains Interval Power Flow typical scene, is able to reflect the annual operation characteristic in planning area, so as to
Uncertain factor is fully considered in planning process, and the conservative caused by the computation interval trend of total state space is avoided to expand
Problem.
Detailed description of the invention
Fig. 1 is the flow chart of the embodiment of the present invention.
Specific embodiment
The present invention will be further described with reference to the accompanying drawings and embodiments.
It is noted that following detailed description is all illustrative, it is intended to provide further instruction to the application.Unless another
It indicates, all technical and scientific terms used herein has usual with the application person of an ordinary skill in the technical field
The identical meanings of understanding.
It should be noted that term used herein above is merely to describe specific embodiment, and be not intended to restricted root
According to the illustrative embodiments of the application.As used herein, unless the context clearly indicates otherwise, otherwise singular
Also it is intended to include plural form, additionally, it should be understood that, when in the present specification using term "comprising" and/or " packet
Include " when, indicate existing characteristics, step, operation, device, component and/or their combination.
As shown in Figure 1, present embodiments providing a kind of Interval Power Flow typical scene construction side based on power curve polymerization
Method, comprising the following steps:
Step S1: enabling one period have L days, provides wind speed, the intensity of illumination data in this period, and by the data generation
Enter into scene power output formula and calculated, obtains all wind of L item, the light day power curve in period；
Step S2: the L wind, light day power curve are expressed as Ni={ ψ (1), ψ (2) ..., ψ (L) }, every curve
All it is a n-dimensional vector, includes that wind-powered electricity generation, the photovoltaic at 24 moment goes out force data；Made with L wind, light day power curve curve
For original sample collection Ni, clusters number K is set, at random from NiChoose a curveAs initial center T(0)In first
Curve；
Step S3: according to formula (1) calculated in remaining sample each curve withEuclidean distanceChoose d
Maximum curve is as Article 2 initial center curveInitial center at this time
In formulaIndicate the distance between curve, ψi(k) the kth dimension data for being curve i,Indicate cluster centre
J-th strip curve；
For remaining sample set Mi(Mi∈Ni/T(0)) every curve is calculated to T(0)The distance of middle curve, takes sum of the distance
Maximum curve is next initial center curve；
The calculating of K maximum distance is executed by the above process, and then obtains K initial cluster center curve
Step S4: original sample collection N is calculatediIt is bent to the middle residual curve for removing cluster centre curve to K cluster centre
The nearest curve of distance in each curve and cluster centre is classified as a kind of scene, thus obtains K curve set by the Euclidean distance of line
It closes, each collection of curves is known as a scene；
Step S5: the average value of every power curve synchronization data in K scene is calculated, new cluster centre is obtained
Curve updates K cluster centre curve；
Step S6: when K cluster centre curve no longer changes, then it is assumed that clustering convergence, L curve sample are divided into K
Class collection of curves, if in each collection of curves including stem curve；Judge whether to reach the condition of convergence；If it is thening follow the steps
S7, otherwise return step S4；
Step S7: cluster sample is made of L wind, light day power curve, and clusters number K value is rangeInterior
Integer executes step S2 to step S6 using different clusters number K, calculates total profile parameters of result after different K values cluster, than
More total profile parameters size selects optimal K value, and executing the K scene that step S2 to S6 is obtained according to the K value is cluster result.
Step S8: according to RDG daily output curve data construction 24 × K group hour power output section in each scene, section is generated
Trend typical scene；
Step S9: it is contributed interval computation Interval Power Flow according to 24 × K group hour that step S8 is obtained.
In the present embodiment, the particular content of the step S1 are as follows:
Wind speed, the intensity of illumination data v in one section of period are providedi,t、hi,t, wherein i=1,2,3 ..., L, L are this section of period
Number of days, 0 < L < 3650, t indicate 24 hours.The data are updated in formula (2) and formula (3) and are calculated.
P in formulawi,tFor the output power of i-th day t-th moment wind-power electricity generation, vi,tIndicate the wind at i-th day t-th moment
Speed, vs、vrAnd v0Respectively indicate rated wind speed, incision wind speed and cut-out wind speed.
P in formulavi,tFor the output power of i-th day t-th moment photovoltaic power generation, hi,tIndicate the reality at i-th day t-th moment
Border intensity of illumination, hrIndicate specified intensity of illumination, PVRFor rated output power.
I-th day wind-powered electricity generation daily output time series data P is calculatedW(i)=(Pwi,1,Pwi,2,…,Pwi,24) and photovoltaic daily output
Time series data PV(i)=(Pvi,1,Pvi,2,…,Pvi,24), merge into wind, the light power curve ψ (i)=[P on the same daywi,1,
Pwi,2,…,Pwi,24,Pvi,1,Pvi,2,…,Pvi,24], obtain L days in period sunrise force curves { ψ (1), ψ (2) ..., ψ
(L)}。
In the present embodiment, the step S7 specifically includes the following contents:
Step S71: cluster sample is made of L wind, light day power curve, and clusters number K value is rangeIt is interior
Integer, step S2 to S6 is executed to sample curve using different K values, obtains corresponding K cluster result；
Step S72: the cluster result after clustering for every kind of K value passes through profile parameters S (ψi) quantization Clustering Effect, wheel
Wide parameter S (ψi) value range be [- 1,1].
A (ψ in formulai) it is cluster condensation degree, indicate the Euclidean distance mean value of other curves in curve and similar scene；b(ψi)
For clustering separation, the Euclidean distance mean value of all curves in curve and other scenes is indicated.
Total profile parameters StIs defined as:
Step S73: compare total profile parameters S that calculating formula (4) and formula (5) obtain under different K values cluster resulttSize,
The maximum cluster result Clustering Effect of total profile parameters is optimal, and corresponding K value is optimum cluster K value, executes step according to the K value
The K scene that S2 to S6 is obtained is cluster result.
In the present embodiment, the step S8 specifically includes the following contents:
Enabling has s RDG sunrise force curve in k-th of scene, as shown in formula (6), the power output sequence of t moment in the scene
Pw,t={ Pwr,t,Pwo,t,...,Pws,t}；By sequence Pw,tGo out that force data is ascending is rearranged for new sequence Y={ y1,
y2,...,ys, sequence Y is handled according to formula (7), by yiWith its intermediate value ziInstead of obtaining sequence Z={ z1,z2,...,
zs}；Using data in sequence Z as foundation, new power output section [minZ, maxZ] is obtained.
Go out force data to 24 hours of the scene by this method to handle, obtains 24 groups of hour wind, light power output area
Between[P in formulaw,1]、[Pv,1] wind-powered electricity generation in scene, photovoltaic are respectively indicated at the 1st moment of the scene
Power output section.Interval structure is carried out to K scene in this way, 24 × K group hour power output section can be obtained；
In the present embodiment, the step S9 specifically includes the following steps:
After obtaining K typical scene by cluster and determine 24 × K group hour power output section, distribution barrier is calculated separately
Between trend.Known power distribution network beginning voltage and end power assume initially that distribution network voltage is all voltage rating, be pushed forward process from
End starts gradually to be pushed forward, and calculates the distribution of the whole network branch power；Back substitution process is gradually pushed back from beginning, calculates each node electricity
Pressure；Constantly repeat be pushed forward with two steps of back substitution, until convergence.
Interval numberWhereinxWithThe respectively lower and upper limit of [X], symbolization [] indicate an area
Between number；The step S9 is all made of interval number and carries out operation, specifically includes the following steps:
Step S91: considering the influence of admittance branch over the ground, and calculate node calculates power:
S in formulaiIndicate that node calculates power, SLiFor node injecting power, yi0For branch admittance over the ground；
Step S92: since distribution network end, being gradually pushed forward, and asks each branch power of power distribution network to be distributed by node voltage.
[S in formulaij] it is branch power, Δ SijFor line power loss, Pj、QjFor node active and reactive power, ZijFor line
Roadlock is anti-, SijFor branch power；
Step S93: node voltage section is asked by branch power
In formulaRespectively indicate the component in length and breadth of branch pressure drop；
Step S94: convergence criterion: iteration ends criterion is the voltage range [U of each nodei] bound is relative to the last time
The numerical bias of iteration is less than permissible value；
In formulaThe respectively voltage magnitude upper and lower bound of kth time interior joint j, ε is deviation allowable value；
Voltage range [the U of each node is obtained after convergencei], i.e. Interval Power Flow calculated result.
The present embodiment is clustered using RDG power curve as sample, construction hour power output section, and then obtains Interval Power Flow
Typical scene is able to reflect the annual operation characteristic in planning area, to fully consider uncertain factor in planning process, and
Avoid the conservative expansion problem caused by the computation interval trend of total state space.In conjunction with specific embodiments, the skill of the present embodiment
Art effect is as shown in table 1.
The Interval Power Flow calculated result of 1 distinct methods of table compares
The present embodiment (1) is regarded RDG power curve as multi-C vector and is carried out using Euclidean distance as similarity judgment criteria
Clustering；
(2) hour power output section structure is proposed based on the noise in median method removal curve for the collection of curves after cluster
Method is made, Interval Power Flow typical scene is generated；
(3) based on the hour power output interval computation Interval Power Flow under typical scene, uncertain problem is handled for power distribution network
Provide technical support.
The foregoing is merely presently preferred embodiments of the present invention, all equivalent changes done according to scope of the present invention patent with
Modification, is all covered by the present invention.
Claims (5)
1. a kind of Interval Power Flow typical scene building method based on power curve polymerization, it is characterised in that: the following steps are included:
Step S1: enabling one period have L days, provides wind speed, the intensity of illumination data in this period, and the data are updated to
It is calculated in scene power output formula, obtains L wind, the light day power curve in period；
Step S2: the L wind, light day power curve are expressed as Ni={ ψ (1), ψ (2) ..., ψ (L) }, every curve is all one
A n-dimensional vector includes that wind-powered electricity generation, the photovoltaic at 24 moment goes out force data；Using L wind, light day power curve as original sample
Collect Ni, clusters number K is set, at random from NiOne curve of middle selectionAs initial center T(0)In first curve；
Step S3: according to formula (1) calculated in remaining sample each curve withEuclidean distanceIt is maximum to choose d
Curve as Article 2 initial center curveInitial center at this time
In formulaIndicate the distance between curve, ψi(k) the kth dimension data for being curve i,Indicate cluster centre j-th strip
Curve；
For remaining sample set Mi(Mi∈Ni/T(0)) every curve is calculated to T(0)The distance of middle curve takes sum of the distance maximum
Curve be next initial center curve；The calculating for executing K maximum distance, obtains K initial cluster center curve
Step S4: original sample collection N is calculatediThe middle residual curve for removing cluster centre curve is to K cluster centre curveEuclidean distance, the nearest curve of distance in each curve and cluster centre is classified as a kind of scene, by
This obtains K collection of curves, and each collection of curves is known as a scene；
Step S5: calculating the average value of every power curve synchronization data in K scene, and it is bent to obtain new cluster centre
Line updates K cluster centre curve；
Step S6: when K cluster centre curve no longer changes, then it is assumed that clustering convergence, it is bent that L curve sample is divided into K class
Line set, if in each collection of curves including stem curve；Judge whether to reach the condition of convergence；It is no if it is thening follow the steps S7
Then return step S4；
Step S7: cluster sample is made of L wind, light day power curve, and clusters number K value is rangeInterior integer,
Step S2 to step S6 is executed using different clusters number K, calculates total profile parameters of result after different K values cluster, it is relatively more total
Profile parameters size selects optimal K value, and executing the K scene that step S2 to S6 is obtained according to the K value is cluster result；
Step S8: according to RDG daily output curve data construction 24 × K group hour power output section in each scene, Interval Power Flow is generated
Typical scene；
Step S9: it is contributed interval computation Interval Power Flow according to 24 × K group hour that step S8 is obtained.
2. a kind of Interval Power Flow typical scene building method based on power curve polymerization according to claim 1, special
Sign is: the particular content of the step S1 are as follows:
Wind speed, the intensity of illumination data v in one period are providedi,t、hi,t, wherein i=1,2,3 ..., L, L are the day in this period
Number, 0 < L < 3650, t indicate 24 hours；The data are updated in formula (2) and formula (3) and are calculated.
P in formulawi,tFor the output power of i-th day t-th moment wind-power electricity generation, vi,tIndicate the wind speed at i-th day t-th moment, vs、
vrAnd v0Respectively indicate rated wind speed, incision wind speed and cut-out wind speed；
P in formulavi,tFor the output power of i-th day t-th moment photovoltaic power generation, hi,tIndicate the practical illumination at i-th day t-th moment
Intensity, hrIndicate specified intensity of illumination, PVRFor rated output power；
I-th day wind-powered electricity generation daily output time series data P is calculatedW(i)=(Pwi,1,Pwi,2,…,Pwi,24) and photovoltaic daily output timing
Data PV(i)=(Pvi,1,Pvi,2,…,Pvi,24), merge into wind, the light power curve ψ (i)=[P on the same daywi,1,Pwi,2,…,
Pwi,24,Pvi,1,Pvi,2,…,Pvi,24], obtain L days sunrise force curves { ψ (1), ψ (2) ..., ψ (L) }.
3. a kind of Interval Power Flow typical scene building method based on power curve polymerization according to claim 1, special
Sign is: the step S7 specifically includes the following contents:
Step S71: cluster sample is made of L wind, light day power curve, and clusters number K value is rangeInterior is whole
Number executes step S2 to S6 to sample curve using different K values, obtains corresponding to K cluster result；
Step S72: the cluster result after clustering for every kind of K value passes through profile parameters S (ψi) quantization Clustering Effect, profile parameters
S(ψi) value range be [- 1,1]；
A (ψ in formulai) it is cluster condensation degree, indicate the Euclidean distance mean value of other curves in curve and similar scene；b(ψi) it is poly-
Class separating degree indicates the Euclidean distance mean value of all curves in curve and other scenes；
Total profile parameters StIs defined as:
Step S73: compare total profile parameters S that calculating formula (4) and formula (5) obtain under different K values cluster resulttSize, total profile
The maximum cluster result Clustering Effect of parameter is optimal, and corresponding K value is optimum cluster K value, executes step S2 to S6 according to the K value
K obtained scene is cluster result.
4. a kind of Interval Power Flow typical scene building method based on power curve polymerization according to claim 1, special
Sign is: the step S8 specifically includes the following contents:
Enabling has s RDG sunrise force curve in k-th of scene, as shown in formula (6), the power output sequence P of t moment in the scenew,t=
{Pwr,t,Pwo,t,...,Pws,t}；By sequence Pw,tGo out that force data is ascending is rearranged for new sequence Y={ y1,
y2,...,ys, sequence Y is handled according to formula (7), by yiWith its intermediate value ziInstead of obtaining sequence Z={ z1,z2,...,
zs}；Using data in sequence Z as foundation, new power output section [minZ, maxZ] is obtained；
Go out force data to 24 hours of the scene to handle, obtains 24 groups of hour RDG power output sections[P in formulardg,i] indicate that RDG is in the power output section at i-th of moment of the scene in scene；According to
Secondary to carry out interval structure to K scene, obtaining 24 × K group hour contributes section.
5. a kind of Interval Power Flow typical scene building method based on power curve polymerization according to claim 1, special
Sign is: the step S9 specifically includes the following steps:
Step S91: calculate node calculates power:
S in formulaiIndicate that node calculates power, SLiFor node injecting power, yi0For branch admittance over the ground；
Step S92: since distribution network end, being gradually pushed forward, and seeks each branch power S of power distribution network by node voltageijDistribution；
[S in formulaij] it is branch power, Δ SijFor line power loss, Pj、QjFor node active and reactive power, ZijFor route resistance
It is anti-, SijFor branch power；
Step S93: node voltage section is asked by branch power
In formulaRespectively indicate the component in length and breadth of branch pressure drop；
Step S94: convergence criterion: iteration ends criterion is the voltage range [U of each nodei] bound is relative to last iteration
Numerical bias be less than permissible value such as formula (15)；
In formulaThe respectively voltage magnitude upper and lower bound of kth time interior joint j, ε is deviation allowable value；
Voltage range [the U of each node is obtained after convergencei], i.e. Interval Power Flow calculated result.
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