CN110165657A - Consider substation's load characteristics clustering analysis method of user's industry attribute - Google Patents
Consider substation's load characteristics clustering analysis method of user's industry attribute Download PDFInfo
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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
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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]
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Abstract
The invention discloses a kind of substation's load characteristics clustering analysis methods for considering user's industry attribute, first by obtaining the load of user and the related data information of industry from marketing system and distribution operating system, then pass through user, distribution transforming, the connection relationship of feeder line and substation carries out topological analysis and realizes that the express statistic of substation's load industry class data summarizes, and clustering is carried out come the load data to statistics by K-means algorithm, the industry of quick obtaining substation load is constituted and is distributed and realizes that the substation's category division for considering load industry attribute has definite meaning.
Description
Technical field
The present invention relates to power system load side pipes to manage technical field, and in particular to a kind of change for considering user's industry attribute
Plant load clustering method.
Background technique
Electric energy can not Mass storage, power generation, transmission of electricity and electricity consumption must carry out simultaneously, therefore keep system hair level
Weighing apparatus is the essential condition of safe and stable operation of power system.It is compared with power generation, transmission of electricity link, system loading side acquisition of information and place
The technological means of reason is then relatively deficient, this results in management and running personnel quickly can not comprehensively understand the load condition of system,
Also the control strategy that is more suitable for can not just be formulated to improve power supply reliability and reduce loss of outage.
Clustering is a kind of statistical analysis technique divided by calculating similarity to data, according to acquired
The data information of description object data are divided into significant cluster or class, so that each member in cluster is known as biggish similitude,
And element then has biggish diversity between cluster, carries out the division for having foundation to large-scale complex data it is possible thereby to realize, thus
Form the conclusion of more illustrative simplicity.
In the load Analysis research of electric system, existing expert and scholar pass through to equipment such as system or substations
Load curve carries out clustering, realizes that the division to magnanimity load data arranges, to be part throttle characteristics research, load prediction
Foundation is analyzed in equal offers.Existing load characteristics clustering analysis is all using based on substation day, the moon or the longer time for measuring acquisition
The total load curve data of span, can not consider the specifying informations such as the industry type of load, and the wave characteristic of load is often
Relevant with specific industry type, the load structure ratio of substation is different, and load variations trend is not also identical, relies solely on
The load value that substation measures can not accurately cluster substation's load.
Summary of the invention
In view of the deficiencies of the prior art, the purpose of the present invention is to provide a kind of substation for considering user's industry attribute is negative
Lotus clustering method, to improve the accuracy of substation's load characteristics clustering analysis.
To achieve the goals above, the technical solution adopted by the present invention is that:
1) in electric power dispatching system, it is end loads that 10kV feeder line, which is all defaulted equivalent, is become without relevant junior's distribution
The user information of depressor information and its power supply, and then there is user data information in existing marketing system, it is therefore desirable to by it
User information data establish feeder line, distribution transforming, user subordinate relation.Wherein, a feeder line can correspond to one or more distribution
Transformer, a distribution transformer can be then one or more customer power supplies, by the operation data and the user that obtain distribution
Information data summarizes the load data for obtaining feeder line, forms feeder line as shown in Table 1-distribution transformer load industry and constitutes statistical form, i.e.,
The load industry of achievable 10kV feeder line constitutes programming count.
1 feeder line of table-distribution transformer load industry constitutes statistical form
2) the network model then subordinate relation containing substation and feeder line for dispatching system, customer charge information summarize to
Behind feeder line end, each disconnecting link position is obtained using the real-time remote signalling data that scheduling system obtains so that it is determined that the connection of network is closed
System can be obtained substation as shown in Table 2-feeder load industry composition statistical form by carrying out topological analysis, complete power transformation
(here by taking 110kV substation as an example, the substation of other voltage class can be like this for the programming count that the load industry stood is constituted
Analogy analysis).
2 substations of table-feeder load industry constitutes statistical form
3) all substation's load industries that scheduling system tune pipe can be counted according to step 1) and 2) constitute data, this
Place primary concern is that substation load industry composition, data prediction is first calculated to the every profession and trade load of substation
Percentage.Here consider N number of substation's sample data { x1, x2... xnIt is divided into K class, it is then concentrated in initial data random
Choose K cluster centre { y1, y2... yk, and iteration ends threshold epsilon and maximum number of iterations M are set, it is determined according to formula (1) every
Classification belonging to a sample data, wherein ciIndicate classification belonging to i-th of sample, d (xi,yj) indicate i-th of sample to jth
The Euclidean distance of a cluster centre, formula (1) indicate sample xiBelonging to makes it to cluster centre apart from that the smallest classification.
ci=arg min [d (xi,yj)] 1≤i≤N,1≤j≤K (1)
4) it obtains existing using formula (2) to arrive the new samples collection that cluster centre distance divides recently for standard by step 3)
New samples concentration redefines new cluster centre, wherein y 'jIndicate that j-th of new cluster centre, m indicate the sample of j-th of cluster
Number,Indicate i-th of sample for belonging to j-th of cluster,
5) after obtaining new cluster centre, judge whether to meet termination condition using formula (3), i.e. front and back cluster centre twice
Distance whether be respectively less than the threshold epsilon of setting and repeat above-mentioned two step until meet termination condition or iteration if being unsatisfactory for
Until the maximum number of iterations M of setting, the cluster result of substation's load data can be obtained,
max[d(y′j,yj)]≤ 1≤j≤K(3)
Compared with prior art, the beneficial effects of the present invention are:
1) Network topology is carried out by means of the electric network model and real-time running data of dispatching system, realizes power transformation
The fast automatic statistics that load industry of standing is constituted；
2) it is clustered using load industry data of the K-means algorithm to substation, calculating fast with calculating speed is again
The low and good advantage of Clustering Effect of miscellaneous degree, and compared to the method for using load curve data to be clustered, this method can be with
Influence of the load of different industries attribute to substation's load is embodied, dividing more has science.
Detailed description of the invention
Fig. 1 is the flow diagram for substation's load characteristics clustering analysis method that the present invention considers user's industry attribute；
Fig. 2 is 10kV feeder line topological relation figure；
Fig. 3 is 110kV substation network topological diagram.
Specific embodiment
The present invention is further illustrated With reference to embodiment.
For the cluster of substation's load, substation's load curve based on measuring value is usually used to be analyzed, but
It is that the load curve of substation can not reflect the part throttle characteristics and variation tendency of substation completely.Part throttle characteristics is often and negative
The industry type of lotus have close correlation, therefore study how the load industry configuration information of quick obtaining substation, and
It is necessary that clustering is carried out to substation using the data.
The present invention proposes a kind of substation's load hierarchical cluster attribute method based on K-means algorithm, by marketing system and matches
The data of net operating system are associated with feeder line, and carry out topology point using the real-time running data of scheduling system and network model
Analysis realizes the express statistic that substation's load industry is constituted, carries out cluster meter using load data of the K-means algorithm to acquisition
It calculates, fast and accurately realizes the statistics and division to substation's load data.This is described in detail below by specific example
The method provided is provided.
1) the distribution transforming information of the user information of marketing system and distribution network systems is associated with the dead-end feeder of scheduling system, is obtained
To dead-end feeder and distribution transforming and the subordinate relation of user, presented using distribution operation data and user information data to summarize
Line-distribution transformer load industry constitutes statistical form, and then the load industry for obtaining feeder line is constituted.Match as shown in Fig. 2, 706 feeder lines are 6
Change is powered, and by obtaining the data of marketing system and distribution network systems, summarizes to obtain feeder load industry composition such as 3 institute of table
Show.
3 706 feeder lines of table-distribution transformer load industry constitutes statistical form (unit: kW)
2) the quick collect statistics that the load data of each feeder line 1) may be implemented through the above steps utilize scheduling system
In operation data determine disconnecting link position and connection relationship after, then carrying out topological analysis by the network model of scheduling system can be with
The load industry for obtaining 110kV substation constitutes data.As shown in figure 3, certain 110kV substation TS1-110 be subordinate's feeder line into
It is available that row power supply, the feeder load information obtained using step 1) and scheduling system real-time running data carry out topological analysis
Substation-feeder load industry constitutes statistical form, and the load industry for summarizing to obtain the substation is constituted as shown in table 4.
4 station TS1-110 of table-feeder load industry constitutes statistical form (unit: kW)
3) load data through the above steps 1) with the station all 110kV of 2) the available scheduling system tune pipe is believed
Breath, it is assumed that include 20 110kV substations in the scheduling system, the load industry of the 110kV substation counted constitutes system
It is as shown in table 5 to count table.
The station 5 110kV of table load industry constitutes statistical form (unit: kW)
Present invention primarily contemplates the industry attributive character of substation's load to carry out clustering, in order to exclude different capabilities
The influence of substation's load value size obtains substation's industry load structure percentage statistical form, such as table according to the data of table 5
Shown in 6.
The station 6 110kV of table load industry component percentage statistical form
It is original sample using above-mentioned data, carries out clustering calculating using K-means algorithm, considered here by sample
It is 4 that data, which are divided into 4 classes i.e. K value, and iteration ends threshold epsilon is 0.0001, and maximum number of iterations M is 300.
4) after the completion of initial setting up, program randomly chooses 4 sample datas and starts to calculate as initial cluster center, according to
Preceding method determines the ownership of sample, and root according to formula (1) by constantly calculating comparative sample at a distance from cluster centre
Cluster centre is constantly updated according to formula (2), until meeting the termination condition of formula (3).4 obtained cluster centres are as shown in table 7, become
The cluster result of plant load data is as shown in table 8.
The station 7 110kV of table load characteristics clustering center table
The station 8 110kV of table load characteristics clustering result table
According to obtained cluster analysis result, A class substation with Commercial Load and resident load for main load structure, B
The specific gravity of resident load is very big in class substation, and C class substation accounts for leading, and D class mainly with agriculture load and resident load
The characteristics of substation's load is that substation all contains a considerable amount of industrial loads.The load area industrial load accounting compared with
It is more, there is the substation close to half to be influenced by industrial load more significant, secondly the variation of resident load also can be to more changeable
Plant load generates certain influence.
To sum up, in order to realize that the quick and precisely clustering of substation's load, the present invention will using the method for topological analysis
The load data information of user carries out automatic collect statistics to obtain the load industry of substation and constitute data, and use to have
The K-means algorithm for the advantages that calculating speed is fast, computation complexity is low, Clustering Effect is good clusters load data.It will be electric
Customer charge information and distribution data information in power marketing system etc. are matched with the 10kV dead-end feeder of major network system, main
The information such as the connection relationship of feeder line and substation are then contained in pessimistic concurrency control, by carrying out Network topology, can quickly be united
The industry of Ji Chu substation is constituted；After being pre-processed to data, using K-means algorithm by constantly calculate comparative sample with
The distance of cluster centre determines that sample belongs to, and searches out the cluster centre met the requirements by iteration, power transformation can be realized
It stands the cluster of load.
Above-listed detailed description is illustrating for possible embodiments of the present invention, and the embodiment is not to limit this hair
Bright the scope of the patents, all equivalence enforcements or change without departing from carried out by the present invention, is intended to be limited solely by the scope of the patents of this case.
Claims (2)
1. a kind of substation's load characteristics clustering analysis method for considering user's industry attribute, which is characterized in that comprising steps of
The distribution transforming information of the user information of marketing system and distribution network systems is associated with the dead-end feeder of scheduling system, is presented
Subordinate relation between line, distribution transforming and user classifies to customer charge according to the subordinate relation and the affiliated industry of user
Statistics, the load industry for obtaining feeder line are constituted；
Real-time remote signalling data is obtained using scheduling system to obtain disconnecting link position so that it is determined that network connection relation, to network connection
Relationship carries out topological analysis and obtains the subordinate relation between substation and feeder line, and then the load industry for obtaining substation is constituted；
The load data of substation is pre-processed, calculates the every profession and trade load percentage of substation and in this, as sample,
Assuming that by the sample { x of N number of substation1, x2... xnIt is divided into K class, K cluster centre is then randomly selected in sample set
{y1, y2... yk, and iteration ends threshold epsilon and maximum number of iterations M are set, class belonging to each sample is determined according to the following formula
Not, wherein ciIndicate classification belonging to i-th of sample, d (xi, yj) indicate i-th of sample to j-th cluster centre it is European away from
From following formula indicates sample xiBelonging to makes it to cluster centre apart from the smallest classification,
ci=arg min [d (xi, yj)] 1≤i≤N, 1≤j≤K
It is obtained by above formula to arrive the new samples collection that cluster centre distance divides recently for standard, is concentrated using following formula in new samples
New cluster centre is redefined, wherein y 'jIndicate that j-th of new cluster centre, m indicate the number of samples of j-th of cluster,Table
Show i-th of sample for belonging to j-th of cluster,
After obtaining new cluster centre, judge whether to meet termination condition using following formula, i.e. the distance of front and back cluster centre twice
It whether is respectively less than the threshold epsilon of setting, if being unsatisfactory for, repeats above-mentioned two step until meeting termination condition or iteration to setting
Maximum number of iterations M until, the cluster result of substation's load data can be obtained,
max[d(y′j, yj)]≤1≤j≤K。
2. the substation's load characteristics clustering analysis method according to claim 1 for considering user's industry attribute, which is characterized in that
Customer charge is divided into industrial load, agriculture load, Commercial Load, resident load and other loads according to affiliated industry.
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| CN115882611A (en) * | 2023-03-08 | 2023-03-31 | 北京清大高科系统控制有限公司 | Ordered electricity utilization monitoring method and device for multi-source data fusion |
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Application publication date: 20190823 |