CN106980925A - A kind of regional power grid dispatching method based on big data - Google Patents
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Abstract
The present invention relates to network load prediction management technical field, a kind of particularly regional power grid dispatching method in big data, including：Step S1, from the electric network information in large database concept data screening is carried out, and the data screened are normalized to form the first aggregation information；Step S2, several information models are pre-established, and the first aggregation information is classified according to information model, to form all kinds of second aggregation informations respectively；Step S3, obtains the characteristic quantity of a corresponding power transmission and transforming equipment, and obtain relative coefficient according to characteristic quantity and the processing of the second aggregation information in every aggregation information of class second；Step S4, handled according to relative coefficient and obtain association status in electric network information between various dimensions, and control is scheduled to each power transmission and transforming equipment according to association status respectively.The beneficial effect of the technical program is：Load management in power network is accurate, the loss in power network can be effectively reduced, so that energy-saving and emission-reduction.
Description
Technical field
The present invention relates to technical field of power grid management, a kind of particularly regional power grid dispatching method based on big data.
Background technology
With the continuous lifting of modern power systems voltage class, the continuous expansion of net capacity, electric power information
Deepen continuously with intelligentized, in local power net, electrical equipment online supervision, intelligent control protection, load management system
Species is more and more, and method is also increasingly advanced, and in long-term, continuous monitoring, control protection, the data volume of collection is very huge
Greatly, and the variation based on method, the data class of collection is also more and more, such as video, image etc., local power net dynamic
Load management system is also being improved constantly to the rate request of data processing, along with traditional method has information gathering in itself
It is single, the problems such as system reliability is poor so that how to integrate Various types of data information, quick effectively analyze data becomes office
One of domain power network dynamic load management system important subject, big data processing method just provides to solve this problem
New idea and method.
So-called big data is that finger with conventional software instrument can not be caught, managed and handled in the range of certain time
Data acquisition system, be to need new tupe to have stronger decision edge, see clearly the sea for finding power and process optimization ability
Amount, high growth rate and diversified information assets.In traditional area power network, load management, energy are dispatched, monitor on-line, supported
Shield etc. is generally all to rarely have the science decision that correlation is carried out by data analysis by the detection of fixed frequency, is less passed through with carrying
The data of magnanimity, i.e. big data carry out effective monitoring in real time and management for power network.
Above-mentioned will have following point in the prior art：
1. the acquisition of electric network information will cause the delayed of decision-making not in time, serious meeting influences the safe operation of power network even
Produce irremediable accident；
2. the very few one-sidedness that will cause to be managed decision-making of information content that power network is obtained；
3. data volume it is excessive will processing data retardance and the insufficiency of data analysis；
4. information processing and decision-making not in time will make it that the electric energy efficiency of transmission in power network is low and wastes huge
The big energy.
The content of the invention
The problem of existing for prior art, the present invention is intended to provide a kind of fast response time, execution efficiency it is high based on
The regional power grid dispatching method of big data, the regional power grid includes power transmission and transforming equipment, wherein, the regional power grid is obtained in advance
In each power transmission and transforming equipment various dimensions electric network information, and set up a large database concept according to all electric network informations, also
Comprise the following steps：
Step S1, from the electric network information in the large database concept carry out data screening, and data to screening
It is normalized to form the first aggregation information；
Step S2, several information models are pre-established, and first aggregation information is entered according to described information model
Row classification, to form all kinds of second aggregation informations respectively, the second aggregation information described in per class includes wrapping in the electric network information
Include the independent variable information in same category；
Step S3, obtains the characteristic quantity of a corresponding power transmission and transforming equipment in the second aggregation information described in every class,
And the second polymerization according to second aggregation information processing of one class of the characteristic quantity and correspondence obtains a corresponding class
Relative coefficient in information between each power transmission and transforming equipment；
Step S4, handled according to the relative coefficient and obtain association status in the electric network information between various dimensions,
And control is scheduled to each power transmission and transforming equipment according to the association status respectively.
Further, in a preferred embodiment of the invention, also include in the step S1：
Step S11, the deletion data unrelated with the regional power grid from the large database concept, and export the first processing number
According to；
Step S12, data noise is removed from first processing data, and export second processing data；
Step S13, handle missing data from the second mathematics data, and export the 3rd processing data；
Step S14, the 3rd processing data is normalized and the first aggregation information is exported.
Further, in a preferred embodiment of the invention, the 3rd processing data substitution following formula is calculated, with
Complete the normalized：
In above formula (1), Y represents result, and X is the 3rd processing data, XminFor in the 3rd processing data
Minimum value, and XmaxFor the maximum in the 3rd processing data.
Further, in a preferred embodiment of the invention, described information model is a kind of CIM (Common
Information Model, common information model), for data related in the large database concept to be classified and contacted；
Described information model includes：
Essential information model, the essential information model includes nominal parameter information and position in the power transmission and transforming equipment
Parameter information；And/or
Life appraisal information model, the life appraisal information model includes the service life letter in the power transmission and transforming equipment
Breath and overload life information；And/or
Status information model, the status information model includes running state information and described in the power transmission and transforming equipment
The status information of environment where power transmission and transforming equipment；And/or
Procedural information model, the procedural information includes the command information for controlling the power transmission and transforming equipment and scheduling is described
The command information of the power of power transmission and transforming equipment；And/or
User side information model, the user side information includes, and user's use demand amount information and power transmission and transforming equipment exist
The output power information of user side.
Further, in a preferred embodiment of the invention, the correlation is obtained by multiple linear relevant function method
Coefficient, obtaining the relative coefficient method is specially：
The independent variable determined in the characteristic quantity and the second aggregation information is substituted into following formula：
In above formula (2), yiFor the characteristic quantity of the power transmission and transforming equipment；b0For the first coefficient correlation, for by described many
The constant calculated in first Linear correlative analysis method；bmFor the relative coefficient；ximFor the independent variable information；Subscript i is
Analysis times, be the independent variable information the multiple linear correlation analysis in analysis times；Subscript m is m
The individual independent variable information, is the single number of the independent variable information；K is the total number of the independent variable information；
And calculate the coefficient correlation.
Further, in a preferred embodiment of the invention, the electric network information includes multiple dimensions, each dimension correspondence
Second aggregation information described in an at least class；
The step S4 is specifically included：
Step S41, predefines the parameter of a dimension, and regard the dimension being determined as need dimension to be processed；
Step S42, selects an independent variable, and choose the independent variable from the second aggregation information described in a class
Multiple dimensions, the multiple dimensions being selected include needing dimension to be processed；
Step S43, Analysis on confidence is carried out according to the relative coefficient, and according to the multiple linear correlation analysis
The weighted value of method output carries out weight analysis, to obtain the relation between the dimension that each is selected, and needs processing
The dimension parameter；
Step S44, judges to need whether the parameter of the dimension to be processed changes：
If so, the step S41 is then returned to, to update the parameter；
Step S45, exports the relation between the dimension that each is selected, and need the ginseng of the dimension to be processed
Amount is scheduled control as output result, and according to the output result to power transmission and transforming equipment each described.
The beneficial effect of the technical program is：The model that gathered data is more, database is complete, analysis is calculated calculates high, prediction
As a result it is accurate so that the load management in power network is accurate, the loss in power network can be effectively reduced, so that energy-saving and emission-reduction.
Brief description of the drawings
Fig. 1 is the flow chart of the regional power grid dispatching method based on big data of the present invention；
Fig. 2 is Fig. 1 step S1 implementation process figures；
Fig. 3 is Fig. 1 step S4 implementation process figures.
Embodiment
The accompanying drawing that lower section will be combined in the embodiment of the present invention, is carried out clear, complete to the technical scheme in the embodiment of the present invention
Site preparation is described, it is clear that described embodiment is only a part of embodiment of the invention, rather than whole embodiments.It is based on
Embodiment in the present invention, those of ordinary skill in the art obtained on the premise of creative work is not made it is all its
His embodiment, belongs to the scope of protection of the invention.
It should be noted that in the case where not conflicting, the embodiment in the present invention and the feature in embodiment can phases
Mutually combination.
Below with the drawings and specific embodiments, the invention will be further described, but not as limiting to the invention.
A kind of regional power grid dispatching method based on big data of the present invention, the execution step of its method is as shown in figure 1, suitable
For regional power grid, regional power grid includes power transmission and transforming equipment, it is characterised in that obtain each power transmission and transforming equipment in regional power grid in advance
Various dimensions electric network information, and set up a large database concept according to all electric network informations, it is further comprising the steps of：
Step S1, data screening is carried out from the electric network information in large database concept, and normalizing is carried out to the data that screen
Change processing to form the first aggregation information；
Step S2, several information models are pre-established, and the first aggregation information is classified according to information model, with
All kinds of second aggregation informations are formed respectively, and often the aggregation information of class second includes being included in electric network information oneself in same category
Variable information；
Step S3, obtains the characteristic quantity of a corresponding power transmission and transforming equipment in every aggregation information of class second, and according to spy
The second aggregation information processing of one class of the amount of levying and correspondence obtains each power transmission and transforming equipment in the corresponding aggregation information of a class second
Between relative coefficient；
Step S4, handled according to relative coefficient and obtain association status in electric network information between various dimensions, and according to pass
Connection state is scheduled control to each power transmission and transforming equipment respectively.
Specifically, in above-mentioned preferred embodiment, because the data volume included in electric network information is big, real-time it is a height of this
Processing information is allowed for by using the data handling procedure in conventional method to slow while the load for reducing power network is adjusted
Spend operational efficiency.
Specifically, in above-mentioned preferred embodiment, step S1 is mainly transformed into by data screening and compression can
The nondimensional normalization data used, data are cleaned, exchanged, compressing and converting is the data that can further polymerize.
Specifically, in above-mentioned preferred embodiment, step S2 is mainly the information model by pre-establishing, and will count greatly
The Data induction included according to storehouse will search further feature amount into data model in data model, and tentatively judge
Relation between corresponding characteristic quantity.
Specifically, in above-mentioned preferred embodiment, step S3 is mainly by multidimensional correlation analysis, it is determined that becoming
Relation between amount.
Specifically, in above-mentioned preferred embodiment, step S4 is that different classes of data are carried out into multidimensional association, is drawn
Required characteristic information, reference is provided for load scheduling.
To sum up, a kind of dispatching method of the regional power grid based on big data, the party are provided in technical scheme
Method is by the way that big data is normalized, correlation analysis, Multidimensional decision-making, solves the unilateral of decision-making in the prior art
Property, control non-timely the problems such as, realize efficient, high reliability the effect of regional power grid load management, production life
The full blast of the optimization that decision-making is enabled to by this strick precaution and decision-making is realized in work, electricity has truly been reached
It is safe and reliable and efficient that net is dispatched.
It is preferred that, in the preferred embodiment, step S1 implementation procedures in step S1 as shown in Fig. 2 also include：
Step S11, the deletion data unrelated with regional power grid from large database concept, and export the first processing data；
Step S12, data noise is removed from the first processing data, and export second processing data；
Step S13, handle missing data from the second mathematics data, and export the 3rd processing data；
Step S14, the 3rd processing data is normalized and the first aggregation information is exported.
Specifically, in above-mentioned preferred embodiment of the invention, in step s 11 it is main by judge data and data it
Between relevance carry out extraneous data and delete choosing, for example, include the place height above sea level of a transformer, the sea in large database concept
Degree of lifting is a kind of unrelated data relative to load scheduling, is that this rejects the height above sea level from data.
Specifically, in the above-mentioned preferred embodiment of the present invention, it is then to judge to be somebody's turn to do that data noise is removed in step s 12
Whether data are in a normal value, for example, the temperature of a certain moment point of the transformer is Celsius for 500 in transformer
Degree, the temperature value, hence it is evident that be not normal temperature value is that the data are judged into noise to remove by this.
Specifically, the present invention above-mentioned preferred embodiment in, missing data is handled in step s 13, then be because
Meeting is possible to when processing data noise the temperature value of such as transformer to deletion, so that partial data vacancy is caused, this
When, it is necessary to be filled up by interpolation method or the median method of average to the data of omission.
It is preferred that, in the preferred embodiment, the 3rd processing data substitution following formula is calculated, to complete to return
One change is handled：
In above formula (1), Y represents result, and X is the 3rd processing data, XminFor in the 3rd processing data
Minimum value, and XmaxFor the maximum in the 3rd processing data.
Specifically, in the above-mentioned preferred embodiments of the present invention, data being substituted into (1) formula and returned with carrying out standard to data
One change is handled, so as to reduce amount of calculation.
It is preferred that, in the preferred embodiment, information model is a kind of CIM (Common Information
Model, common information model), for data related in large database concept to be classified and contacted；Information model includes：
Essential information model, essential information model includes nominal parameter information and location parameter letter in power transmission and transforming equipment
Breath；And/or
Life appraisal information model, life appraisal information model includes the service life information and mistake in power transmission and transforming equipment
Carry life information；And/or
Status information model, status information model includes running state information and power transmission and transforming equipment institute in power transmission and transforming equipment
In the status information of environment；And/or
Procedural information model, procedural information includes the command information of control power transmission and transforming equipment and dispatches power transmission and transforming equipment
The command information of power；And/or
User side information model, user side information includes, and user's use demand amount information and power transmission and transforming equipment are in user
The output power information of side.
Specifically, in above-mentioned preferred embodiment of the invention, because CIM is used as a kind of data mark known to one kind
Quasi-ization pattern, it represents power system resource specifically by a kind of relation with object class and attribute and between them is provided
Standard method, CIM facilitate realize different user or power network stand-alone development EMS (EMS) application it is integrated,
It is integrated between the complete EMS system of multiple stand-alone developments, and EMS system and other not Tongfangs for being related to Operation of Electric Systems
The system in face, such as it is integrated between generating or distribution system.
It is preferred that, in the preferred embodiment, relative coefficient is obtained by multiple linear relevant function method, obtained
The relative coefficient method is taken to be specially：
The independent variable determined in characteristic quantity and the second aggregation information is substituted into following formula：
In above formula (2), yiFor the characteristic quantity of the power transmission and transforming equipment；b0For the first coefficient correlation, for by described many
The constant calculated in first Linear correlative analysis method；bmFor the relative coefficient；ximFor the independent variable information；Subscript i is
Analysis times, be the independent variable information the multiple linear correlation analysis in analysis times；Subscript m is m
The individual independent variable information, is the single number of the independent variable information；K is the total number of the independent variable information；
And calculate coefficient correlation.
Specifically, in above-mentioned preferred embodiment of the invention, multiple linear relevant function method solves the pass between variable
System, is a kind of widely used technological means to those skilled in the art.
It is preferred that, in the preferred embodiment, electric network information includes multiple dimensions, each dimension correspondence at least one
The aggregation information of class second；
Step S4 is specifically included：
Step S41, predefines the parameter of a dimension, and regard the dimension being determined as need dimension to be processed；
Step S42, selects an independent variable, and choose multiple dimensions of independent variable, quilt from second aggregation information of class
The multiple dimensions chosen include needing dimension to be processed；
Step S43, Analysis on confidence is carried out according to relative coefficient, and according to the output of multiple linear relevant function method
Weighted value carries out weight analysis, to obtain the relation between the dimension that each is selected, and needs the parameter of dimension to be processed；
Step S44, judges to need whether the parameter of dimension to be processed changes：
If so, then return to step S41, to update parameter；
Step S45, exports the relation between the dimension that each is selected, and need the parameter of dimension to be processed as defeated
Go out result, and control is scheduled to each power transmission and transforming equipment according to output result.
Specifically, in above-mentioned preferred embodiment of the invention, being described further below in conjunction with Fig. 3 to step S4：
If in view of three-dimensional scheduling association state, it is assumed that three dimensions are respectively Z axis：Load operation dimension, Y
Axle：Information dimension and X-axis：Time dimension, wherein load operation dimension includes：Life appraisal, load condition；Information dimension bag
Include：Essential information, on-line monitoring related information, power scheduling information and historical failure information；Time dimension includes：Electrical quantity is supervised
Survey, process variable is monitored, quantity of state is monitored and weather monitoring.
Step S41：Predefine the parameter of a dimension, and using the dimension being determined as needing dimension to be processed, this
When Z axis is defined as to need dimension to be processed.
Step S42：An independent variable is selected from second aggregation information of class, and chooses multiple dimensions of independent variable, quilt
The multiple dimensions chosen include needing dimension to be processed, are now analyzed Y-axis and X-axis as independent variable.
Step S43：Analysis on confidence is carried out according to relative coefficient, and according to the output of multiple linear relevant function method
Weighted value carries out weight analysis, to obtain the relation between the dimension that each is selected, and needs the parameter of dimension to be processed,
The coefficient correlation determined in the multidimensional correlation analysis method according to progress in step s3, and weight is now needed to be weighed
Weight analysis, so that corresponding relation is obtained, while it will be recognized by those skilled in the art that weight analysis can be using subjective tax
A kind of progress weight analysis in Quan Fa, objective weighted model, Evaluation formula.
Step S44：Judge to need whether the parameter of dimension to be processed changes：If so, then return to step S41, with more
New parameter.
Step S45：The relation between the dimension that each is selected is exported, and needs the parameter of dimension to be processed as defeated
Go out result, and control is scheduled to each power transmission and transforming equipment according to output result.
Preferred embodiments of the present invention are these are only, embodiments of the present invention and protection domain is not thereby limited, it is right
For those skilled in the art, it should can appreciate that all utilization description of the invention and being equal made by diagramatic content replace
Change and obviously change resulting scheme, should be included in protection scope of the present invention.
Claims (6)
1. a kind of regional power grid dispatching method based on big data, it is adaptable to regional power grid, the regional power grid includes power transmission and transformation
Equipment, it is characterised in that obtain the electric network information of the various dimensions of each power transmission and transforming equipment in the regional power grid, and root in advance
A large database concept is set up according to all electric network informations, it is further comprising the steps of：
Step S1, data screening is carried out from the electric network information in the large database concept, and the data that screen are carried out
Normalized is to form the first aggregation information；
Step S2, several information models are pre-established, and first aggregation information is divided according to described information model
Class, to form all kinds of second aggregation informations respectively, the second aggregation information described in per class includes being included in the electric network information
Independent variable information in same category；
Step S3, obtains the characteristic quantity of a corresponding power transmission and transforming equipment, and root in the second aggregation information described in every class
The second aggregation information described in a corresponding class is obtained according to second aggregation information processing of one class of the characteristic quantity and correspondence
In relative coefficient between each power transmission and transforming equipment；
Step S4, handled according to the relative coefficient and obtain association status in the electric network information between various dimensions, and root
Control is scheduled to each power transmission and transforming equipment respectively according to the association status.
2. the regional power grid dispatching method according to claim 1 based on big data, it is characterised in that in the step S1
Also include：
Step S11, the deletion data unrelated with the regional power grid from the large database concept, and export the first processing data；
Step S12, data noise is removed from first processing data, and export second processing data；
Step S13, handle missing data from the second mathematics data, and export the 3rd processing data；
Step S14, the 3rd processing data is normalized and the first aggregation information is exported.
3. the regional power grid dispatching method according to claim 2 based on big data, it is characterised in that at the described 3rd
Reason data substitute into following formula and calculated, to complete the normalized：
In above formula (1), Y represents result, and X is the 3rd processing data, XminFor the minimum in the 3rd processing data
Value, and XmaxFor the maximum in the 3rd processing data.
4. the regional power grid dispatching method according to claim 1 based on big data, it is characterised in that described information model
For a kind of common information model, for data related in the large database concept to be classified and contacted；Described information model
Including：
Essential information model, the essential information model includes nominal parameter information and location parameter in the power transmission and transforming equipment
Information；And/or
Life appraisal information model, the life appraisal information model include the power transmission and transforming equipment in service life information with
And overload life information；And/or
Status information model, the status information model includes running state information and the defeated change in the power transmission and transforming equipment
The status information of environment where electric equipment；And/or
Procedural information model, the procedural information includes the command information for controlling the power transmission and transforming equipment and dispatches the defeated change
The command information of the power of electric equipment；And/or
User side information model, the user side information includes, and user's use demand amount information and power transmission and transforming equipment are in user
The output power information of side.
5. the regional power grid dispatching method according to claim 1 based on big data, it is characterised in that pass through multiple linear
Relevant function method obtains the relative coefficient, obtains the relative coefficient method and is specially：
The independent variable information determined in the characteristic quantity and the second aggregation information is substituted into following formula：
In above formula (2), yiFor the characteristic quantity of the power transmission and transforming equipment；
b0For the first coefficient correlation, to pass through the constant calculated in the multiple linear relevant function method；
bmFor the relative coefficient；
ximFor the independent variable information；
Subscript i be analysis times, be the independent variable information the multiple linear correlation analysis in analysis times；
Subscript m is independent variable information described in m-th, is the single number of the independent variable information；
K is the total number of the independent variable information；
And calculate the relative coefficient.
6. the regional power grid dispatching method as claimed in claim 5 based on big data, it is characterised in that the electric network information bag
Include multiple dimensions, the second aggregation information described in each dimension correspondence at least class；
The step S4 is specifically included：
Step S41, predefines the parameter of a dimension, and regard the dimension being determined as need dimension to be processed；
Step S42, selects an independent variable, and choose the multiple of the independent variable from the second aggregation information described in a class
Dimension, the multiple dimensions being selected include needing dimension to be processed；
Step S43, Analysis on confidence is carried out according to the relative coefficient, and defeated according to the multiple linear relevant function method
The weighted value that goes out carries out weight analysis, to obtain the relation between the dimension that each is selected, and needs institute to be processed
State the parameter of dimension；
Step S44, judges to need whether the parameter of the dimension to be processed changes：
If so, the step S41 is then returned to, to update the parameter；
Step S45, exports the relation between the dimension that each is selected, and need the parameter of the dimension to be processed to make
For output result, and control is scheduled to power transmission and transforming equipment each described according to the output result.
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