CN103440539B - A kind of user power utilization data processing method - Google Patents
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Abstract
The embodiment of the invention discloses a kind of user power utilization data processing method, described method includes: obtain each user uses electrical feature；According to clustering with electrical feature of described each user, obtain multiple bunches；Obtain target bunch, described target bunch be targeted customer place bunch；Obtain bunch index of target bunch；Industry index according to targeted customer place industry and bunch index of target bunch, obtain the fellow peers' evaluation index of targeted customer, to carry out targeted customer with electrically optimized according to described fellow peers' evaluation index.The embodiment of the present invention from each user of user power utilization extracting data with electrical feature and cluster, realize targeted customer's personal feature is accurately positioned, the fellow peers' evaluation index of the targeted customer by obtaining, targeted customer is carried out Comprehensive Correlation with other similar users and relevant industries index, thus contribute to subsequent treatment carries out quantitative evaluation to optimizing power consumption plan, it is possible to it is effectively improved accuracy and the relevance grade optimizing electricity consumption.
Description
Technical field
The embodiment of the present invention relates generally to power domain, especially relates to a kind of user power utilization data process side
Method.
Background technology
High energy-consuming enterprises the most all can expend a large amount of electric energy when producing, and major part enterprise is not to electricity consumption at present
Process is optimized, and adds the production cost of enterprise, reduces enterprise profit, does not also meet country
Energy-saving and emission-reduction policy.In the prior art, optimize electricity consumption to rely primarily on power department customer manager and pass through to walk
Visit user and sampling survey is carried out, based on factors such as user's average electricity price, load factors, by manual point
Analysis business electrical situation, draws optimization electricity consumption suggestion.This mode not only subjective factors is relatively big, and only
Be analyzed for single business electrical situation, it is provided that lack comprehensively the when of Optimizing Suggestions, have for
The data support of property.
Inventor finds during realizing the present invention, along with the development of intelligent grid and intelligent electric meter
Universal, existing electrical network large user substantially has been carried out all standing, entirely gathers, and meanwhile, have accumulated a large amount of
User power utilization data.For these valuable user power utilization data, still lack a kind of effective process
Scheme, to help the quantitative analysis carried out by electrically optimized aspect.
Summary of the invention
In view of this, the purpose of the embodiment of the present invention is to provide a kind of user power utilization data processing method, with
Contribute to the quantitative analysis by electrically optimized aspect.
The embodiment of the invention discloses a kind of user power utilization data processing method, described method includes:
Obtain each user uses electrical feature；
According to clustering with electrical feature of described each user, obtain multiple bunches；
Obtain target bunch, described target bunch be targeted customer place bunch；
Obtain bunch index of target bunch；
Industry index according to targeted customer place industry and bunch index of target bunch, obtain targeted customer's
Fellow peers' evaluation index, to carry out with electrically optimized targeted customer according to described fellow peers' evaluation index；
The project phase that wherein said electrical feature, bunch index, industry index, fellow peers' evaluation index are comprised
With.
Preferably, described electrical feature, bunch index, industry index, fellow peers' evaluation index all comprise following
One or more: affiliated industry, production order of classes or grades at school, maximum load, rate of load condensate, average electricity price, capacity-load ratio.
Preferably, described clustering with electrical feature according to each user, obtain multiple bunches, including:
It is characterized as that vector sets up initial fuzzy Fuzzy matrix with the electricity consumption of each user；
By described Fuzzy matrix standardization, obtain normalized matrix；
The similarity coefficient of each user is obtained according to described normalized matrix；
Sorting procedure is performed a plurality of times, and to obtain multiple bunches, described sorting procedure includes: produce random number
μ (μ ∈ [0,1]), according to described random number acquisition fixed value λ as horizontal classification, will be greater than described fixed value
User gather for cluster.
Preferably, the described industry index according to targeted customer place industry and bunch index of target bunch, obtain
Take the fellow peers' evaluation index of targeted customer, including:
Pass through following formula
xi=α × xui+(1-α)×xci (α∈[0,1])
Obtain the fellow peers' evaluation index of targeted customer, wherein xuiFor i-th in industry index, xciFor bunch
In index i-th, xiFor i-th in fellow peers' evaluation index, α is used for regulating xuiAnd xciWeight,
So that industry index and a bunch index are revised mutually.
Preferably,
When Time,
Wherein | C | is the total number of users in targeted customer place bunch, and | N | is targeted customer in the industry
Total number of users.
The embodiment of the invention also discloses a kind of user power utilization data handling system, described system includes:
Use electrical feature acquiring unit, use electrical feature for obtain each user；
Cluster cell, for clustering with electrical feature according to described each user, obtains multiple bunches；
Target bunch acquiring unit, is used for obtaining target bunch, described target bunch be targeted customer place bunch；
Bunch index selection unit, for obtaining bunch index of target bunch；
Fellow peers' evaluation index selection unit, for the industry index according to targeted customer place industry and target
Bunch bunch index, obtain targeted customer fellow peers' evaluation index, with according to described fellow peers' evaluation index to mesh
Mark user is carried out with electrically optimized；
The project phase that wherein said electrical feature, bunch index, industry index, fellow peers' evaluation index are comprised
With.
Preferably, described electrical feature, bunch index, industry index, fellow peers' evaluation index all comprise following
One or more: affiliated industry, production order of classes or grades at school, maximum load, rate of load condensate, average electricity price, capacity-load ratio.
Preferably, described cluster cell includes:
Fuzzy matrix builds subelement, initial fuzzy for being characterized as that vector is set up with the electricity consumption of each user
Fuzzy matrix；
Normalizer unit, for by described Fuzzy matrix standardization, obtains normalized matrix；
Similarity coefficient obtains subelement, for obtaining the similarity coefficient of each user according to described normalized matrix；
Cluster control subelement, for repeatedly driving cluster subelement, to obtain multiple bunches；
Cluster subelement, is used for producing random number μ (μ ∈ [0,1]), obtains fixed value λ according to described random number
As horizontal classification, the user that will be greater than described fixed value gathers for cluster.
Preferably, described fellow peers' evaluation index selection unit is especially by following formula
xi=α × xui+(1-α)×xci (α∈[0,1])
Obtain the fellow peers' evaluation index of targeted customer, wherein xuiFor i-th in industry index, xciFor bunch
In index i-th, xiFor i-th in fellow peers' evaluation index, α is used for regulating xuiAnd xciWeight,
So that industry index and a bunch index are revised mutually.
Preferably,
When Time,
Wherein | C | is the total number of users in targeted customer place bunch, and | N | is targeted customer in the industry
Total number of users.
The embodiment of the present invention from each user of user power utilization extracting data with electrical feature and cluster, look for
To targeted customer place bunch, i.e. find the user similar to targeted customer, it is achieved individual to targeted customer
Being accurately positioned of feature, by the fellow peers' evaluation index of targeted customer obtained, by targeted customer and other
Similar users and relevant industries index carry out Comprehensive Correlation, thus contribute to using optimizing in subsequent treatment
Electricity scheme carries out quantitative evaluation, contributes to analyzing the suggestion of user optimization electricity consumption, it is possible to be effectively improved excellent
Change accuracy and the relevance grade of electricity consumption.
Accompanying drawing explanation
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 reality
Execute the required accompanying drawing used in example or description of the prior art to be briefly described, it should be apparent that below,
Accompanying drawing in description is only some embodiments of the present invention, for those of ordinary skill in the art,
On the premise of not paying creative work, it is also possible to obtain other accompanying drawing according to these accompanying drawings.
Fig. 1 is the flow chart that the embodiment of the present invention one method is described；
Fig. 2 is the flow chart that the embodiment of the present invention two method is described；
Fig. 3 is the schematic diagram that the embodiment of the present invention four system is described.
Detailed description of the invention
Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is carried out
Clearly and completely describe, it is clear that described embodiment is only a part of embodiment of the present invention, and
It is not all, of embodiment.Based on the embodiment in the present invention, those of ordinary skill in the art are not making
Go out the every other embodiment obtained under creative work premise, broadly fall into the scope of protection of the invention.
In order to understand the present invention comprehensively, refer to numerous concrete details in the following detailed description, but
It should be appreciated by those skilled in the art that the present invention can realize without these details.Real at other
Execute in example, be not described in detail known method, process, assembly and circuit, in order to avoid undesirably resulting in reality
Execute example to obscure.
Embodiment one
Fig. 1 is the flow chart of the embodiment of the present invention one method.Present embodiment discloses a kind of user power utilization number
According to processing method, described method includes:
S101, obtain each user use electrical feature.Development along with information technology, it is already possible to collect
Substantial amounts of user power utilization data, the present embodiment is in order to make full use of these electricity consumption data, it is proposed that user's
By this concept of electrical feature.User's is the basis of the present invention with electrical feature, as the term suggests can be understood as
Embody some indexs of user power utilization characteristic, data, such as, can include with next or many with electrical feature
Individual project: affiliated industry, production order of classes or grades at school, maximum load, rate of load condensate, average electricity price, capacity-load ratio, etc.
Deng.
S102, clustering with electrical feature according to described each user, obtain multiple bunches.The use of each user
Electrical feature mixes and defines larger data group, and this data group can be carried out cluster analysis,
Each user is divided into bunch, makes similar user return together.Concrete clustering method the present embodiment is not carried out
Limit, it is possible to use data are clustered by existing various clustering algorithms.
S103, obtain target bunch, described target bunch be targeted customer place bunch.Targeted customer is the most current
It is analyzed the user optimized.
S104, bunch index of acquisition target bunch.Bunch index refers to carry out each user after cluster obtains bunch,
For the indices of this bunch that certain bunch calculates, as a bunch average electricity price (with in user power utilization feature
Average electricity price corresponding) etc..
S105, according to the industry index of targeted customer place industry and bunch index of target bunch, obtain target
The fellow peers' evaluation index of user, to carry out with electrically optimized targeted customer according to described fellow peers' evaluation index；
The project that described electrical feature, bunch index, industry index, fellow peers' evaluation index are comprised is identical.
Industry index can be to be categorized as benchmark with GB_T4754-2002 industry standard, in certain industry
The indices drawn, such as industry average electricity price etc..Fellow peers' evaluation refers to using user in electrical feature
Every indices with its place industry contrasts.
Inventor finds during realizing the present invention, in relating to the relevant application that mark is compared of industry,
It is all using the situation of whole industry as standard, and have ignored different scope of the enterprise and with user under electrical feature
Individual diversity, so the Optimizing Suggestions proposed lacks customization, relevance grade is the highest, and the present embodiment
By the way of cluster, it is divided into a class to be analyzed similar user, the accuracy of analysis can be improved,
Overcome and lack customization, problem that relevance grade is the highest.
The fellow peers' evaluation index of targeted customer is to be wanted after user power utilization data are processed by the present embodiment
The final result obtained, has had fellow peers' evaluation index just to contribute in subsequent treatment entering optimizing power consumption plan
Row quantitative evaluation, contributes to analyzing the point of user optimization electricity consumption, the final raising standard of electrically optimized analysis
Exactness and relevance grade.Further, it is also possible to further in conjunction with parameters such as power rate standards, comprehensive this use of analysis
The energy-saving potential at family and electricity consumption prioritization scheme.
Embodiment two
Fig. 2 is the flow chart of the embodiment of the present invention two method.The present embodiment, based on embodiment one, is to reality
Execute the further refinement of example one.In the present embodiment, for step S102 i.e. according to described each user's
Cluster with electrical feature, obtain multiple bunches, when being embodied as, can take following optimal way:
S1021, it is characterized as that vector sets up initial fuzzy Fuzzy matrix with the electricity consumption of each user.Assume sample
Set N comprises k object (that is one user of an object) n1、n2、…、nk, and each right
As having m attribute, (in an i.e. user power utilization feature of attribute, a user uses electrical feature
In one vector of every composition), all vector composition Nk×mMatrix, its element can use xijRepresent,
I=1,2 ..., k, j=1,2 ..., m.
S1022, by described Fuzzy matrix standardization, obtain normalized matrix.After being calculated standardization
The each element of k × m, thus obtain normalized matrix Rk×m.For each element in normalized matrix
rij, can be calculated by equation below:
S1023, according to described normalized matrix obtain each user similarity coefficient.Concrete, for phase
Like the demarcation of coefficient, quantity area method can be used:
Wherein TijRepresent i-th user and the similarity of jth user.
S1024, sorting procedure being performed a plurality of times, to obtain multiple bunches, described sorting procedure includes: produce
Random number μ (μ ∈ [0,1]), according to described random number acquisition fixed value λ as horizontal classification, will be greater than described
The user of fixed value gathers for cluster.When being embodied as, T can be found outijTwo elements maximum in matrix,
It is designated as T(1)+T(2), then by λ=(1-μ)+T(1)+T(2)Calculate λ.
Embodiment three
The present embodiment, based on embodiment one, is the further refinement to embodiment one.In the present embodiment,
For step S105 i.e. according to industry index and bunch index of target bunch of targeted customer place industry, obtain
Take the fellow peers' evaluation index of targeted customer, when being embodied as, can take following optimal way:
Pass through following formula
xi=α × xui+(1-α)×xci (α∈[0,1])
Obtain the fellow peers' evaluation index of targeted customer, wherein xuiFor i-th in industry index, xciFor bunch
In index i-th, xiFor i-th in fellow peers' evaluation index, α is used for regulating xuiAnd xciWeight,
So that industry index and a bunch index are revised mutually.
Additionally, when total number of users | the C | in targeted customer place bunch targeted customer user in the industry
When sum | N | occupies the minority, illustrate that this bunch has stronger particularity, targeted customer in whole industry
Electricity consumption situation be more prone to and the contrast of bunch index；Otherwise this refers to reference to industry more then to show targeted customer
Mark.It is preferred based on above-mentioned consideration,
When Time,
Wherein | C | is the total number of users in targeted customer place bunch, the user that | N | is targeted customer in the industry
Sum.
Embodiment four
Fig. 3 is the schematic diagram of the embodiment of the present invention four system.The present embodiment is relative with said method embodiment
Should, disclosing a kind of user power utilization data handling system 300, described system 300 includes:
With electrical feature acquiring unit 301, use electrical feature for obtain each user；
Cluster cell 302, for clustering with electrical feature according to described each user, obtains multiple bunches；
Target bunch acquiring unit 303, is used for obtaining target bunch, and described target bunch is targeted customer place
Bunch；
Bunch index selection unit 304, for obtaining bunch index of target bunch；
Fellow peers' evaluation index selection unit 305, for according to the industry index of targeted customer place industry and
Bunch index of target bunch, obtains the fellow peers' evaluation index of targeted customer, with according to described fellow peers' evaluation index
Targeted customer is carried out with electrically optimized；
The project phase that wherein said electrical feature, bunch index, industry index, fellow peers' evaluation index are comprised
With.
Preferably, described electrical feature, bunch index, industry index, fellow peers' evaluation index all comprise following
One or more: affiliated industry, production order of classes or grades at school, maximum load, rate of load condensate, average electricity price, capacity-load ratio.
Preferably, described cluster cell 302 includes:
Fuzzy matrix builds subelement, initial fuzzy for being characterized as that vector is set up with the electricity consumption of each user
Fuzzy matrix；
Normalizer unit, for by described Fuzzy matrix standardization, obtains normalized matrix；
Similarity coefficient obtains subelement, for obtaining the similarity coefficient of each user according to described normalized matrix；
Cluster control subelement, for repeatedly driving cluster subelement, to obtain multiple bunches；
Cluster subelement, is used for producing random number μ (μ ∈ [0,1]), obtains fixed value λ according to described random number
As horizontal classification, the user that will be greater than described fixed value gathers for cluster.
Preferably, described fellow peers' evaluation index selection unit 305 is especially by following formula
xi=α × xui+(1-α)×xci (α∈[0,1])
Obtain the fellow peers' evaluation index of targeted customer, wherein xuiFor i-th in industry index, xciFor bunch
In index i-th, xiFor i-th in fellow peers' evaluation index, α is used for regulating xuiAnd xciWeight,
So that industry index and a bunch index are revised mutually.
Preferably,
When Time,
Wherein | C | is the total number of users in targeted customer place bunch, and | N | is targeted customer in the industry
Total number of users.
For system embodiment, owing to it corresponds essentially to embodiment of the method, so relevant part ginseng
See that the part of embodiment of the method illustrates.System embodiment described above is only schematically,
The wherein said unit illustrated as separating component can be or may not be physically separate, makees
The parts shown for unit can be or may not be physical location, i.e. may be located at a place,
Or can also be distributed on multiple NE.Can select according to the actual needs part therein or
The whole module of person realizes the purpose of the present embodiment scheme.Those of ordinary skill in the art are not paying creation
Property work in the case of, be i.e. appreciated that and implement.
Also, it should be noted in this article, the relational terms of such as first and second or the like is only used
One entity or operation are separated with another entity or operating space, and not necessarily requires or secretly
Show relation or the order that there is any this reality between these entities or operation.And, term " bag
Include ", " comprising " or its any other variant be intended to comprising of nonexcludability, so that bag
Include the process of a series of key element, method, article or equipment and not only include those key elements, but also include
Other key elements being not expressly set out, or also include for this process, method, article or equipment
Intrinsic key element.In the case of there is no more restriction, statement " including ... " limit
Key element, it is not excluded that there is also additionally in including the process of described key element, method, article or equipment
Identical element.
The foregoing is only presently preferred embodiments of the present invention, be not intended to limit the protection model of the present invention
Enclose.Specific case used herein has carried out lock stated principle and the embodiment of the present invention, above reality
The explanation executing example is only intended to help to understand method and the core concept thereof of the present invention；Simultaneously for ability
The those skilled in the art in territory, according to the thought of the present invention, the most all can
Change part.In sum, this specification content should not be construed as limitation of the present invention.All at this
Any modification, equivalent substitution and improvement etc. made within the spirit of invention and principle, are all contained in this
In bright protection domain.
Claims (3)
1. a user power utilization data processing method, it is characterised in that described method includes:
Obtain each user uses electrical feature；
According to clustering with electrical feature of described each user, obtain multiple bunches；
Obtain target bunch, described target bunch be targeted customer place bunch；
Obtain bunch index of target bunch；
Industry index according to targeted customer place industry and bunch index of target bunch, obtain targeted customer's
Fellow peers' evaluation index, to carry out with electrically optimized targeted customer according to described fellow peers' evaluation index；
The project phase that wherein said electrical feature, bunch index, industry index, fellow peers' evaluation index are comprised
With；
Described clustering with electrical feature according to each user, obtains multiple bunches, including:
It is characterized as that vector sets up initial fuzzy Fuzzy matrix with the electricity consumption of each user；
By described Fuzzy matrix standardization, obtain normalized matrix；
The similarity coefficient of each user is obtained according to described normalized matrix；
Sorting procedure is performed a plurality of times, and to obtain multiple bunches, described sorting procedure includes: produce random number
μ, μ ∈ [0,1], according to described random number acquisition fixed value λ as horizontal classification, will be greater than described fixed value
User gathers for cluster；
Described electrical feature, bunch index, industry index, fellow peers' evaluation index all comprise with the next item down or many
: affiliated industry, production order of classes or grades at school, maximum load, rate of load condensate, average electricity price, capacity-load ratio.
Method the most according to claim 1, it is characterised in that described be expert at according to targeted customer
The industry index of industry and bunch index of target bunch, obtain the fellow peers' evaluation index of targeted customer, including:
Pass through following formula
xi=α × xui+(1-α)×xci,α∈[0,1]
Obtain the fellow peers' evaluation index of targeted customer, wherein xuiFor i-th in industry index, xciFor bunch
In index i-th, xiFor i-th in fellow peers' evaluation index, α is used for regulating xuiAnd xciWeight,
So that industry index and a bunch index are revised mutually.
Method the most according to claim 2, it is characterised in that
WhenTime,
Wherein | C | is the total number of users in targeted customer place bunch, and | N | is targeted customer in the industry
Total number of users.
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| CN104240144B (en) * | 2014-08-25 | 2017-12-22 | 河海大学 | A kind of power load aggregation method based on demand response |
| CN104794234B (en) * | 2015-05-06 | 2019-02-15 | 华北电力大学 | Data processing method and device for fellow peers' evaluation |
| CN105184479A (en) * | 2015-09-01 | 2015-12-23 | 广州地理研究所 | Urban resident water-consumption behavior classification method based on intelligent water meter |
| CN106651630B (en) * | 2016-09-27 | 2019-09-27 | 中国南方电网有限责任公司电网技术研究中心 | Key electricity utilization industry identification method and system |
| CN106845874B (en) * | 2017-03-16 | 2020-09-08 | 北京中电普华信息技术有限公司 | Relevance calculation method and device |
| CN108776939A (en) * | 2018-06-07 | 2018-11-09 | 上海电气分布式能源科技有限公司 | The analysis method and system of user power utilization behavior |
| CN110163527A (en) * | 2019-05-31 | 2019-08-23 | 国网上海市电力公司 | A kind of enterprise's energy intellectual analysis management method |
| CN111160489A (en) * | 2020-01-02 | 2020-05-15 | 中冶赛迪重庆信息技术有限公司 | Multi-dimensional benchmarking analysis server, system and method based on big data and electronic terminal |
| CN112215526B (en) * | 2020-11-05 | 2023-11-10 | 国网重庆市电力公司营销服务中心 | Metering system evaluation method and device and readable storage medium |
| CN113837597B (en) * | 2021-09-22 | 2024-03-29 | 广东电网有限责任公司 | Analysis method, device, equipment and storage medium for electricity utilization opposite-standard mining |
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| CN101620619A (en) * | 2009-08-07 | 2010-01-06 | 北京航空航天大学 | System and method for processing gross error of measuring data based on clustering method |
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