CN106529731A - Regional power grid photovoltaic power station cluster division method - Google Patents
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Abstract
The invention discloses a regional power grid photovoltaic power station cluster division method and belongs to the photovoltaic generation technology field. The method comprises steps that the initial output power data of a photovoltaic power station is acquired, an output power sequence is acquired, a cluster division index set is calculated, a cluster division model is established, multitime clustering for the photovoltaic power station is carried out, clustering discretivity of multiple clustering evaluation indexes is calculated, a smallest value clustering result of clustering discretivity of the multiple clustering evaluation indexes is selected as a cluster division result of the photovoltaic power station. The method is advantaged in that the initial output power data of the photovoltaic power station is employed to carry out cluster division for the photovoltaic power station, compared with a division method on the basis of a geographic position distance of the photovoltaic power station, the division result acquired through employing the initial output power data of the photovoltaic power station can actually reflect actual output characteristics of the photovoltaic power station, improvement of accuracy of a program design prediction model can be facilitated, and dependence of a prediction model on data completeness of a single photovoltaic power station can be reduced.
Description
Technical field
The present invention relates to technical field of photovoltaic power generation, more particularly to a kind of regional power grid photovoltaic plant assemblage classification side
Method.
Background technology
In short supply with global fossil energy, the intermittent energy source such as photovoltaic generation has worldwide obtained quick sending out
Exhibition.Photovoltaic plant is a kind of photovoltaic generating system, and it is a kind of using solar energy, using special material such as crystal silicon plate, inverse
Become the generating system of the electronic components such as device composition.Photovoltaic plant is connected with electrical network and is transmitted electric power to electrical network.With China's photovoltaic
What is generated electricity develops rapidly, it will the situation that a large amount of photovoltaic plants are constructed and put into operation in the short time occur, while also bringing along a series of
Problem.
In photovoltaic plant planning and designing, staff is needed to be exerted oneself by meteorologic factors such as irradiation level to determine according to photovoltaic
The optimal installation site of photovoltaic plant and installed capacity.Now need to consume substantial amounts of human resources and computing resource to photovoltaic electric
Preparation of standing is built the history meteorological data in ground area and carries out substantial amounts of simulation analysis.For prediction modeling, if to each photovoltaic
Power station is predicted modeling, it will consume a large amount of calculating storage resources.Simultaneously as newly build a power station lacking local historical data
Accumulation, newly-built power station data completeness are low, cause precision of forecasting model poor.
Power producing characteristics more than existing photovoltaic plant planning and designing using photovoltaic plant carry out assemblage classification to which, according to light
The power producing characteristics of overhead utility are found out and representative in certain geography scope go out force mode.According to assemblage classification result choose with
Website to be predicted has other photovoltaic plants of similar power producing characteristics, and carries out power prediction using the correlation between them,
The prediction modeling difficulty of photovoltaic plant can be also reduced, while meeting the requirement of precision of forecasting model.Therefore adopt photovoltaic plant collection
The mode that group divides greatly reduces the workload of photovoltaic plant Site Selection, accelerates the construction process of photovoltaic plant.Photovoltaic
The reasonable assemblage classification of station group is conducive to shortening the completion time of project, saves computing resource, reduces regional prediction model to single light
The dependence of overhead utility data extrapolating.
However, existing photovoltaic plant assemblage classification method carries out drawing according only to the distance on photovoltaic plant geographical position
Point, partitioning standards are excessively single, and division result can not truly reflect the actual power producing characteristics of each photovoltaic plant, therefore urgently seek
Look for a kind of more scientific rational photovoltaic plant assemblage classification method.
The content of the invention
The invention provides a kind of regional power grid photovoltaic plant assemblage classification method, to solve photovoltaic plant in prior art
Assemblage classification method is divided only in accordance with photovoltaic plant geographical position, and division result cannot truly reflect each photovoltaic plant
Actual power producing characteristics, cause the problem of regional prediction model accuracy difference.
In order to solve above-mentioned technical problem, the embodiment of the invention discloses following technical scheme：
A kind of regional power grid photovoltaic plant assemblage classification method, regional power grid photovoltaic plant assemblage classification method include：Adopt
The initial output power data of collection photovoltaic plant, obtain power output sequence；Divided according to power output sequence computing cluster and referred to
Mark collection；Assemblage classification model is set up according to assemblage classification index set；Photovoltaic plant is repeatedly gathered according to assemblage classification model
Class；Multiple Cluster Assessment indexs are calculated according to multiple cluster result and cluster dispersions, choose multiple Cluster Assessment indexs cluster from
Result of the minimum cluster result of numerical value as the assemblage classification of photovoltaic plant in divergence.
Preferably, the initial output power data of photovoltaic plant are gathered, the method for obtaining power output sequence includes：To first
Beginning power output data are normalized, and obtain normalized power output sequence.
Preferably, the method for calculating photovoltaic plant assemblage classification index set according to power output sequence includes：
The characteristic parameter of the power output sequence of photovoltaic plant is extracted, the assemblage classification eigenmatrix of photovoltaic plant is formed；
Photovoltaic plant assemblage classification index set is obtained according to assemblage classification eigenmatrix.
Preferably, characteristic parameter includes the degree of bias of average stability bandwidth, capacity factor, power maximum and power output.
Preferably, the method for setting up assemblage classification model according to assemblage classification index set is included, is calculated using K-means clusters
Assemblage classification index set is calculated assemblage classification model by method, wherein, the cluster numbers of K-means clustering algorithms are 4 classes.
Preferably, in repeatedly being clustered to photovoltaic plant using assemblage classification model, clustered in repeatedly clustering every time
Initial cluster center is different.
A kind of regional power grid photovoltaic plant assemblage classification method provided from above technical scheme, the present invention, including
The initial output power data of collection photovoltaic plant, obtain power output sequence；Divided according to power output sequence computing cluster
Index set；Assemblage classification model is set up according to assemblage classification index set；Photovoltaic plant is carried out repeatedly according to assemblage classification model
Cluster；Multiple Cluster Assessment indexs are calculated according to multiple cluster result and clusters dispersion, choose multiple Cluster Assessment index clusters
Result of the minimum cluster result of numerical value as the assemblage classification of photovoltaic plant in dispersion.Present invention employs photovoltaic electric
The initial output power data stood carry out assemblage classification to photovoltaic plant, compared to according to the far and near division in photovoltaic plant geographical position
Method, the division result obtained using photovoltaic plant initial output power can truly reflect actually exerting oneself for each photovoltaic plant
Characteristic, is conducive to improving the accuracy of photovoltaic plant planning and designing forecast model, reduces forecast model to single photovoltaic plant
The dependence of data extrapolating.
Description of the drawings
In order to be illustrated more clearly that the embodiment of the present invention or technical scheme of the prior art, below will be to embodiment or existing
Accompanying drawing to be used needed for having technology description is briefly described, it should be apparent that, for those of ordinary skill in the art
Speech, on the premise of not paying creative work, can be with according to these other accompanying drawings of accompanying drawings acquisition.
Fig. 1 is a kind of regional power grid photovoltaic plant assemblage classification method flow schematic diagram provided in an embodiment of the present invention.
Specific embodiment
In order that those skilled in the art more fully understand the technical scheme in the present invention, below in conjunction with of the invention real
The accompanying drawing in example is applied, the technical scheme in the embodiment of the present invention is clearly and completely described, it is clear that described enforcement
Example is only a part of embodiment of the invention, rather than the embodiment of whole.Based on the embodiment in the present invention, this area is common
The every other embodiment obtained under the premise of creative work is not made by technical staff, should all belong to protection of the present invention
Scope.
Fig. 1 is a kind of regional power grid photovoltaic plant assemblage classification method flow schematic diagram provided in an embodiment of the present invention, by
Fig. 1 understands that regional power grid photovoltaic plant assemblage classification method includes：
S101：The initial output power data of collection photovoltaic plant, obtain power output sequence；
Wherein, the initial output power data of photovoltaic plant are gathered, the method for obtaining power output sequence includes：To initial
Power output data are normalized, and obtain normalized power output sequence.Concretely comprise the following steps：To each photovoltaic plant
Power output data in certain period of time are acquired, and the power output data for collecting are designated as Pi, i=1,2 ..., n,
Wherein i=1,2 ..., n is photovoltaic plant sequence number, and n represents the sum of photovoltaic plant, PiRepresent serial numberiPhotovoltaic plant it is initial
Power output sequence.Initial output power sequence P of each photovoltaic plantiCorrespondence power station power samples point set { pi(t1),pi
(t2),...,pi(tN), wherein tj, j=1,2 ..., N represent the collection moment of each power samples point, and N represents the photovoltaic plant
Power output data sampling point number, p in this timei(tj) represent serial number i photovoltaic plant tjThe power output at moment.
In order to eliminate the impact caused to division result because different installeds capacity of power station are different, by the initial of photovoltaic plant
Power output data are normalized, and normalization formula is as follows：
Wherein, PiThe photovoltaic plant initial output power sequence that numbering is i is represented,Represent that the installation of the photovoltaic plant is held
Amount.Pi* it is the power output sequence after normalization, the power station power samples point set corresponding to which is combined into
S102：According to power output sequence computing cluster Classification Index collection；
Wherein, the method for calculating photovoltaic plant assemblage classification index set according to power output sequence includes：Extract photovoltaic electric
The characteristic parameter of the power output sequence stood, forms the assemblage classification eigenmatrix of photovoltaic plant；According to assemblage classification feature square
Battle array obtains photovoltaic plant assemblage classification index set.Characteristic parameter includes average stability bandwidth, capacity factor, power maximum and output
The degree of bias of power.Concretely comprise the following steps：
Power output sequence P to each photovoltaic planti *, i=1,2 ..., n, extract following characteristic parameter to form photovoltaic
The assemblage classification eigenmatrix in power station：
A, average stability bandwidth
WhereinThe i.e. average stability bandwidth of first feature of i-th photovoltaic plant is represented,Represent tjThe power output sequence of i-th photovoltaic plant of moment, N represent the number of power samples point；
B, capacity factor
WhereinThe second feature i.e. capacity factor of i-th photovoltaic plant is represented,Represent
tjThe power output sequence of i-th photovoltaic plant of moment, N represent the number of power samples point；
C, power maximum
WhereinRepresent the 3rd feature i.e. work(of i-th photovoltaic plant
Rate maximum,Represent tjThe power output sequence of i-th photovoltaic plant of moment, N represent the number of power samples point；
The degree of bias of d, power output
WhereinRepresent tjI-th photovoltaic plant of moment it is defeated
Go out power, N represents the number of power samples point,Represent power station power samples point setIt is flat
Average, s represent the standard deviation of sampled point set；
Each photovoltaic plant can be described by the characteristic vector that aforementioned four feature is constituted, wherein i-th power station
Characteristic vector be represented by Fi={ Fi 1,Fi 2,Fi 3,Fi 4, then all of photovoltaic plant can composition characteristic matrix F.F can be by under
Formula is calculated：Eigenmatrix F is photovoltaic plant assemblage classification index set.
S103：Assemblage classification model is set up according to assemblage classification index set；
Wherein, the method for setting up assemblage classification model according to assemblage classification index set includes：Using K-means clustering algorithms
Assemblage classification index set is calculated into assemblage classification model, the cluster numbers of K-means clustering algorithms are 4 classes.Specially：
Using the photovoltaic plant eigenmatrix F determined in step S102 as input, set up based on K-means clustering algorithms
The result of photovoltaic plant assemblage classification is designated as C={ C by photovoltaic plant assemblage classification model1,C2,…,CK, whereinRepresent the cluster centre of k-th cluster.Which can pass through to calculate what is included in kth class
The characteristic vector of all photovoltaic plants is averagely worth to.
S104：Photovoltaic plant is repeatedly clustered according to assemblage classification model；
Wherein, in repeatedly being clustered to photovoltaic plant using assemblage classification model, what is clustered in repeatedly clustering every time is first
Beginning cluster centre is different.In the present embodiment, M cluster is carried out to photovoltaic plant using assemblage classification model.
S105：Multiple Cluster Assessment indexs are calculated according to multiple cluster result and clusters dispersion, choose multiple Cluster Assessments
Result of the minimum cluster result of numerical value as the assemblage classification of photovoltaic plant in index cluster dispersion.
Specially：Using Cluster Assessment index cluster dispersion (Clustering Dispersion Indicator,
CDI) cluster result is evaluated, its computing formula is as follows：
WhereinThe average distance between each cluster centre is represented, distance adopts Europe
Formula distance is calculated, and wherein the distance between kth class cluster centre and -1 class cluster centre of kth can be calculated by following formula：
Wherein,Represent the
Average distance between each photovoltaic plant characteristic vector that i classes are included, wherein in such between m-th and m-1
Distance is：
Repeat step S103 to S105M time, and the initial cluster center of K-means is randomly selected every time, choose this M time and gather
In class result a minimum cluster result of Cluster Assessment index cluster dispersion index as photovoltaic plant assemblage classification most
Termination fruit, completes the assemblage classification to photovoltaic plant.
The initial output power data that present invention employs photovoltaic plant carry out assemblage classification to photovoltaic plant, compared to root
According to photovoltaic plant geographical position distance division methods, the division result obtained using photovoltaic plant initial output power can be true
Reflect the actual power producing characteristics of each photovoltaic plant, be conducive to improving the accuracy of photovoltaic plant planning and designing forecast model, subtract
Dependence of the forecast model to single photovoltaic plant data extrapolating is lacked.
The description of the embodiment of the method by more than, those skilled in the art can be understood that the present invention can
By software plus required general hardware platform mode realizing, naturally it is also possible to by hardware, but in many cases the former
It is more preferably embodiment.Based on such understanding, technical scheme substantially makes tribute to prior art in other words
The part offered can be embodied in the form of software product, and the computer software product is stored in a storage medium, bag
Include some instructions to use so that a computer equipment (can be personal computer, server, or network equipment etc.) performs
The all or part of step of each embodiment methods described of the invention.And aforesaid storage medium includes：Read-only storage
(ROM), random access memory (RAM), magnetic disc or CD etc. are various can be with the medium of store program codes.
Each embodiment in this specification is described by the way of progressive, identical similar portion between each embodiment
Divide mutually referring to what each embodiment was stressed is the difference with other embodiment.Especially for device or
For system embodiment, as which is substantially similar to embodiment of the method, so describing fairly simple, related part is referring to method
The part explanation of embodiment.Apparatus and system embodiment described above is only schematic, wherein the conduct
Separating component explanation unit can be or may not be it is physically separate, as the part that unit shows can be or
Person may not be physical location, you can local to be located at one, or can also be distributed on multiple NEs.Can be with root
Factually border need select some or all of module therein to realize the purpose of this embodiment scheme.Ordinary skill
Personnel are not in the case where creative work is paid, you can to understand and implement.
It should be noted that herein, the relational terms of such as " first " and " second " or the like are used merely to one
Individual entity or operation are made a distinction with another entity or operation, and are not necessarily required or implied these entities or operate it
Between there is any this actual relation or order.And, term " including ", "comprising" or its any other variant are intended to
Cover including for nonexcludability, so that a series of process, method, article or equipment including key elements not only includes those
Key element, but also including other key elements being not expressly set out, or also include for this process, method, article or set
Standby intrinsic key element.In the absence of more restrictions, the key element for being limited by sentence "including a ...", it is not excluded that
Also there is other identical element in the process including the key element, method, article or equipment.
The above is only the specific embodiment of the present invention, it is noted that for the ordinary skill people of the art
For member, under the premise without departing from the principles of the invention, some improvements and modifications can also be made, these improvements and modifications also should
It is considered as protection scope of the present invention.
Claims (6)
1. a kind of regional power grid photovoltaic plant assemblage classification method, it is characterised in that the regional power grid photovoltaic plant cluster is drawn
Point method includes：
The initial output power data of collection photovoltaic plant, obtain power output sequence；
According to the power output sequence computing cluster Classification Index collection；
Assemblage classification model is set up according to the assemblage classification index set；
Photovoltaic plant is repeatedly clustered according to the assemblage classification model；
Multiple Cluster Assessment indexs are calculated according to the multiple cluster result and clusters dispersion, chosen the plurality of Cluster Assessment and refer to
Result of the minimum cluster result of numerical value as the assemblage classification of photovoltaic plant in mark cluster dispersion.
2. a kind of regional power grid photovoltaic plant assemblage classification method according to claim 1, it is characterised in that the collection
The initial output power data of photovoltaic plant, the method for obtaining power output sequence include：To the initial output power data
It is normalized, obtains normalized power output sequence.
3. a kind of regional power grid photovoltaic plant assemblage classification method according to claim 1, it is characterised in that the basis
The power output sequence calculates the method for photovoltaic plant assemblage classification index set to be included：
The characteristic parameter of the power output sequence of the photovoltaic plant is extracted, the assemblage classification eigenmatrix of photovoltaic plant is formed；
The photovoltaic plant assemblage classification index set is obtained according to the assemblage classification eigenmatrix.
4. a kind of regional power grid photovoltaic plant assemblage classification method according to claim 3, it is characterised in that the feature
Parameter includes the degree of bias of average stability bandwidth, capacity factor, power maximum and power output.
5. a kind of regional power grid photovoltaic plant assemblage classification method according to claim 4, it is characterised in that according to described
Assemblage classification index set sets up the method for assemblage classification model to be included, refers to the assemblage classification using K-means clustering algorithms
Mark collection is calculated the assemblage classification model, wherein, the cluster numbers of the K-means clustering algorithms are 4 classes.
6. a kind of regional power grid photovoltaic plant assemblage classification method according to claim 1, it is characterised in that the utilization
During the assemblage classification model is repeatedly clustered to photovoltaic plant, the initial cluster center for being clustered in the multiple cluster every time
It is different.
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