A kind of platform area topology identification method accelerated based on NB-IoT and GPU
Technical field
The present invention relates to grid topology data administrative skill field, especially a kind of platform accelerated based on NB-IoT and GPU
Area's topology identification method.
Background technique
Platform area transformer is the last one transformer that electric power energy reaches that user is passed through, and is not only carry high-voltage electricity
It is transformed to the energy conversion task of low pressure alternating current, secondary concentrator equipment, which also carries, collects user in its supply district
Power information task is the dual hubbed of energy and information.
However, as being continuously increased for power load causes the variation of electric power facility to adjust (such as to relocate, dilatation, cutover, cloth
Point etc.), grid company can be because various technical reasons, management lack of standardization or power and responsibility adjustment etc. be made during the operation of many years
It does not conform to the actual conditions at ammeter archives and the platform area ownership of ground cable power supply user defines and is difficult to the accounts entanglement problem such as determining.
(that is: which customer power supply a transformer gives on earth, is confused about;Certain user be on earth by which transformer-supplied,
It is confused about;Being commonly called as the change of platform area can not find ammeter, and ammeter can not find the change of platform area.)
Accurately basis account, be carry out platform area line loss per unit analysis, three-phase imbalance analysis with improvement, Distribution Network Failure it is fixed
Position, repairing work order issue etc. a series of important foundation of advanced applications, and State Grid Corporation of China is referred to as " battalion is with perforation ", i.e.,
Marketing system and distribution network systems share a set of database, realize that data information sharing and service optimization Collaboration are matched by battalion.
State Grid Corporation of China pays special attention to the combing work of distribution basis account in recent years, spent a large amount of human and material resources,
Financial resources are for seeking with perforation.Technical solution that there are two main classes:
A uses external accessory:
Main means are to implement tactics of human sea, one by one platform using a kind of Hand apparatus for being referred to as " platform area penetrates through instrument "
Family table carries out perforation test, combs in turn one by one in area.
Major drawbacks existing for this method are to expend a large amount of manpower and material resources and inefficient, and combing achievement is difficult to maintain, when
Power grid architecture changes again and manages record work when there is careless mistake, still will appear that account is chaotic, topology is unclear asks
Topic, needs manually to penetrate through again.
B uses the carrier communication module with identification capability:
Carrier technology is a kind of currently the only communication technology propagated along a power circuit, with power network topology point
Cloth is closely related, and recognizing automatically to family variable topological relationship has natural advantage.Current power information acquisition system is largely equal
There are Some Enterprises to start with from carrier communication module using power line carrier technology, therefore also, has developed with platform family identification capability
Bandwidth carrier module.
However, carrier technology for identification major drawbacks be still to have the area's problem that gets two or more radio stations at once, carrier signal by altogether,
High pressure, the mode of parallel routing coupling remain to and neighbouring to the area Zhou Biantai transmission data although signal amplitude is decayed altogether
The ammeter being closer under transformer is communicated.
In recent years, some scholars analyze the data of intelligent electric meter using the relevant technologies of big data, to carry out
The topology Identification in platform area.But since data are huge, intelligent electric meter Numerous, these efficiency of algorithm are relatively low, Bu Nengman
The on line real time of the area Zu Tai topology, associated higher application are accordingly restricted.
Summary of the invention
It is an object of the present invention on the one hand need to realize the accurate recognition of platform area topology in conjunction with transformer and electricity
The mass data of table carries out data dependence analysis, promotes the accuracy of identification;On the other hand, it in order to promote computational efficiency, solves
Certainly based on the identification of platform area topology and to the higher associated higher application demand of requirement of real-time, to data dependence analysis algorithm
In can be parallel dependency structure and step carry out parallel acceleration processing, to further increase the whole efficiency of algorithm.
Realize that the technical solution of the object of the invention is as follows:
A kind of area's topology Identification method, including
Step 1: the voltage fluctuation of the manufacture area l Tai Tai step down side;
Step 2: the n moment within a period acquires the area l Tai Tai step down side voltage respectively and m platform is to be identified
Electric supply meter voltage, obtain corresponding reference sequence Xj={ xj(k) | k=1,2 ..., n } and compare ordered series of numbers Xi={ xi
(k) | k=1,2 ..., n }, wherein j=1,2 ..., l;I=1,2 ... m;
Step 3: to reference sequence and comparing ordered series of numbers progress without guiding principleization processing, i.e.,With
Step 4: calculating separately the incidence coefficient of each reference sequence ordered series of numbers corresponding element compared with each
In formula, ρ=0.5 is resolution ratio,
Δxj,i(k)=| x'j(k)-xi' (k) |,
Step 5: calculating separately the degree of association γ of each reference sequence ordered series of numbers compared with eachj,i,
The degree of association γj,iIndicate the degree of association of i-th electric supply meter voltage Yu the area jTai Tai transformer voltage;
Step 6: the successively degree of association of more every electric supply meter voltage and every area Tai Tai transformer voltage: as i-th with
The degree of association highest of family meter voltage and all areas area transformer ZhongjTai Tai transformer voltage then determines i-th user
Ammeter is by the area jTai Tai transformer-supplied;
Described area's transformer and electric supply meter access the power information system based on NB-IoT Internet of Things, pass through NB-
IoT communication carrys out the voltage of picking platform area step down side voltage and electric supply meter to be identified;
Above-mentioned steps accelerate to handle parallel using based on GPU:
Wherein,
It calculatesIt calculatesCalculate Δ xj,i(k)=| x'j(k)-x'i(k) | and calculateN thread block is enabled, enables m thread in per thread block;
It calculatesAnd calculatingWhen, to thereinWithM thread block is enabled, enables 1 thread in per thread block;
It calculatesM thread block is enabled, enables 1 thread in per thread block.
Further, the method for the voltage fluctuation of the manufacture platform area step down side are as follows: it is high to change platform area transformer
Side bus voltage is pressed, or changes low appearance impedance configuration in parallel, or change platform area load tap changer, or install SVG additional.Above-mentioned skill
The further technical solution of art scheme are as follows: further include recording collected area's step down side voltage in the step 2
It is separate;It further include with the separate to have determined that as the electric supply meter of described area's transformer-supplied of record in the step 6
Affiliated is separate.
The beneficial effects of the present invention are metric data and step down side to intelligent electric meter at each user measure number
According to analysis is associated, to measure the similarity between user's intelligent electric meter data and step down side intelligent electric meter data,
To identify the affiliated platform area of user and separate, evades and a large amount of manpower and material resources have been expended using " platform area penetrates through instrument " and using carrying
Wave technology get two or more radio stations at once area the problem of, the area Shi Tai topology identification it is more accurate and convenient.Based on similarity algorithm, improves platform area and open up
Flutter the accuracy of identification.Parallel algorithm based on GPU accelerates similarity calculation, and more traditional CPU serial algorithm is compared,
Efficiency of algorithm significantly improves, and for some large-scale examples, speed-up ratio can reach thousands of times.Therefore, the platform accelerated based on GPU
The demand that area's topology Identification method can sufficiently adapt to the analysis of magnanimity high density data and calculate meets the knowledge of online platform area topology
Other requirement of real-time.
Detailed description of the invention
Fig. 1 is the grey correlation analysis algorithm flow chart accelerated based on GPU.
Specific embodiment
A specific embodiment of the invention is further explained below.
There is determining electrical connection, becoming in radius of electricity supply in platform area can ignore between platform area transformer and electric supply meter
Line drop, therefore the voltage of user side is bound to increase with the raising of the exit potential of platform area change, the two has height
Correlation, variation tendency height is consistent.For example, transformer of manually stopping transport, the family table having a power failure therewith then centainly belongs to this area
Become power supply;Conversely, the transformer that manually puts into operation, the family table powered on therewith can reaffirm that belonging to this area becomes power supply.But
This method engineering is huge time-consuming and laborious, not only brings not small loss to Utilities Electric Co., in power off notifying situation not in place early period
Under be also possible to lead to civil disputation.
Power distribution station user is that radial topological mode is run, and due to the difference of different moments load, voltage is at user
Now certain fluctuation status.But in the same separate user in same area, electrical distance is closer, voltage fluctuation rule
With very strong similitude;And the user in area, electrical distance be not remote on the same stage for category, voltage fluctuation similitude is poor.According to this
Principle is primarily based on NB-IoT and obtains the higher user side voltage big data of sample frequency, voltage fluctuation history curve correlation point
Analysis provides big data support.Further, by changing high side bus voltage, changing the low appearance impedance configuration of parallel connection, change
The artificial fluctuating range for increasing voltage of the methods of load tap changer, installation SVG, or even manufacture have the voltage of certain rule bent
Line.Analysis is associated to the metric data and step down side metric data of intelligent electric meter at each user, to measure user
Similarity between intelligent electric meter data and step down side intelligent electric meter data, to identify the affiliated Tai Qu of user and phase
, do not evaded using " platform area perforation instrument " expend a large amount of manpower and material resources and using carrier technology get two or more radio stations at once area the problem of, the area Shi Tai
Topology identification is more accurate and convenient.
The present invention is based on above-mentioned principle, starts with from the ammeter communication module of user side, using NB-IoT technology conduct
Communication modes obtain the higher user side voltage big data of sample frequency, bent by the voltage fluctuation history with platform area transformer
Line carries out correlation analysis, clustering, to solve the problems, such as platform area topology Identification.In order to improve the accuracy of identification, pass through change
The artificial increase electricity of the methods of high side bus voltage, change low appearance impedance configuration in parallel, change load tap changer, installation SVG
The fluctuating range of pressure, or even manufacture have the voltage curve of certain rule.
Following methods are used when specific implementation:
Step 1: by changing high side bus voltage, change low appearance impedance configuration in parallel, change load tap changer, adding
Fill the artificial fluctuating range for increasing voltage of the methods of SVG.
Step 2: using NB-IoT technology as communication modes, obtaining highdensity area and become exit potential and user side electricity
Press data.
Step 3: passing through the metric data and step down side metric data progress grey to intelligent electric meter at each user
Association analysis, to measure the similarity between user's intelligent electric meter data and step down side intelligent electric meter data, to know
The affiliated platform area of other user and separate.
The basic thought of grey correlation is using the data sequence of factor as foundation, between the technique study factor of mathematics
The geometry of geometrical correspondence, i.e. sequence curve is closer, then their grey relational grade is bigger.It unites compared to mathematics
The data analysing methods such as regression analysis, the Principal component analysis of meter, this method are few to sample size demand, also do not need sample and meet
The typical regularity of distribution, and its calculation amount is smaller.
The present invention is associated analysis, specific steps using the metric data that gray relative analysis method acquires intelligent electric meter
It is as follows:
1) reference sequence X is chosenj={ xj(k) | k=1,2 ..., n }, j=1,2 ..., l, the ordered series of numbers X compared withi={ xi
(k) | k=1,2 ..., n }, i=1,2 ... m.Wherein, n is moment number, and l is the number of reference sequence, and m is to compare ordered series of numbers
Number.Here, reference sequence is the metric data of the area l Tai Tai step down side voltage, and comparing ordered series of numbers is that m platform is to be identified
The metric data of the voltage of electric supply meter.
2) reference sequence is carried out with ordered series of numbers is compared without guiding principleization processing.
3) incidence coefficient of each relatively ordered series of numbers and each reference sequence corresponding element is calculated separately according to the following formula
In formula, ρ is resolution ratio, usually takes 0.5.Wherein, Δ xj,i(k)=| x'j(k)-x'i(k)|。
4) degree of association γ of each relatively ordered series of numbers and parameter ordered series of numbers is found out according to the following formulaj,i。
Finally, it by the degree of association between user's intelligent electric meter data and step down side intelligent electric meter data, realizes
The identification of platform area topology precise and high efficiency.Such as i-th electric supply meter voltage and all areas area transformer ZhongjTai Tai transformer electricity
The degree of association highest of pressure then determines i-th electric supply meter by the area jTai Tai transformer-supplied.
In recent years, with increasingly mature, GPU (the Graphics Processing Unit graphics process of semiconductor technology
Device) it is developed rapidly.GPU is different from CPU, and control unit therein and memory proportion are seldom, and arithmetic element institute
Accounting example is very big, therefore has powerful computing capability.Originally, GPU is mainly used for graphical display, and with NVIDIA company
The one kind released for 2007 new programming model and instruction set architecture CUDA (Compute Unified Devices
Architecture), GPU general-purpose computations are also gradually applied to the calculating field of subjects.
Under the frame of CUDA, user can define kernel function, executed parallel when calling n times n it is different parallel
Thread is completed identical kernel function for different data and is instructed.Each kernel function occupies a thread net when calling
Network (Grid), per thread network are made of multiple thread blocks (Block), are executed parallel between each thread block.Each thread
Block includes multiple threads (Thread) again, is executed parallel between each thread.When calling kernel function, the line of enabling can be set
The number of threads enabled in journey number of blocks and per thread block.
When being associated analysis using the metric data that gray relative analysis method acquires intelligent electric meter, the concurrency of algorithm
It embodies as shown in the table:
As seen from the above table, all have can concurrency for all multi-steps of Grey Relation Algorithm.Difference relatively ordered series of numbers can be parallel
It is the parallel of coarseness, each relatively ordered series of numbers is mutually indepedent, and no relation of interdependence is only mutually calculated with reference sequence,
Therefore parallel processing can be implemented in the related calculating between different comparison ordered series of numbers.It is same relatively ordered series of numbers different moments can be parallel
Be it is fine-grained parallel, some calculating need to be respectively processed the voltage data of different moments, and when handling and other when
The voltage data at quarter is unrelated, such as without guiding principle processing, the calculating of incidence coefficient, seek absolute value as difference, therefore this part is counted
Parallel processing can also be implemented between different moments by calculating step.
It is analyzed according to above-mentioned concurrency, a series of GPU kernel functions can be designed, be used to parallel acceleration total algorithm.
The design of kernel function, shown in table specific as follows:
Wherein, kernel function 1,3 enables n thread block respectively, m thread is enabled in per thread block, thus each ratio
Data compared with each moment of ordered series of numbers can carry out calculation processing parallel;Kernel function 2,4 enables m thread block respectively, each
1 thread is enabled in thread block, so that each relatively ordered series of numbers carries out calculation processing parallel.
By above-mentioned processing, on the basis of carrying out platform area topology Identification based on similarity algorithm, it is based on GPU parallel algorithm
Similarity calculation is accelerated, the demand for sufficiently adapting to the analysis of magnanimity high density data and calculating, meets online platform area topology
The requirement of real-time of identification.