CN106356994A - Grid stability judging method based on grid PMU big data - Google Patents
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Abstract
The invention relates to a grid stability judging method based on grid PMU big data, and belongs to two fields of grid big data analysis and grid stability analysis. The method comprises the following steps: firstly, performing modeling according to grid PMU data through a random matrix; secondly, analyzing grid PMU historical data, and establishing a distribution up and down boundary map of the PMU historical data; thirdly, analyzing grid PMU real-time data, and establishing a characteristic value distribution map of the PMU real-time data; fourthly, displaying and comparing the characteristic value distribution map of the PMU real-time data and the distribution up and down boundary map of the PMU historical data on the same interface, so as to judge whether a grid is stable or not. According to the method, the grid stability is cognized according to statistic characteristics, such as the PMU historical data and the PMU real-time data, and the requirements of the grid, and can be displayed through a human-computer interface, so that the grid is convenient for a grid operation and maintenance administrator to use.
Description
Technical field
The present invention relates to the analysis of electrical network big data and two fields of power grid stability analysis, it is based on electrical network particularly to a kind of
The grid stability method of discrimination of pmu big data.
Background technology
The development of intelligent grid is maked rapid progress, and its corresponding intelligent grid new technique also continues to bring out.The topology knot of electrical network
Structure also more sophisticated, the stable operation of intelligent grid needs to meet following condition: the foundational system of electrical network and Related Supporting Technologies,
Unpredictable external disturbance can be resisted enough；Electrical network need in time prediction it may happen that fault, and assess this fault
The impact that electrical network may be produced, being beneficial to electrical network can be with Quick fault, isolated fault；The compatibility of electrical network will be got well, energy
Adapt to the access of the charge-discharge facility such as distributed micro-capacitance sensor in a large number and withdraw；The O＆M cost of intelligent grid is controlled, electrical network
Operation state visualization is high, in order to provide corresponding control implementing measure and counte-rplan.
In order to be better understood from and analyze electrical network, a large amount of pmu are disposed in electrical network, with obtain more, approximately with
The electrical network O＆M information (more than the 20 kind of data such as voltage in real-time grid, electric current, power and phase angle) of step.Pmu is wide in electrical network
General layout is for more preferable cognitive electrical network, simplifies the analysis process of electrical network.Huge electric network state data is to intelligent grid
Analysis brings probability, meanwhile, also Challenge.For example: how substantial amounts of pmu data utilizes, how to combine reality
Electric network data analyzes corresponding practical problem；Can be obtained any information from substantial amounts of pmu data；From a large amount of electric network datas
Whether the information obtaining can visualize, and facilitate electrical network operation management person to use.
The huge pmu data analysiss of power system can be seen as a big data system.Electrical network big data is to divide in recent years
One focus of analysis.Big data, as a gated data science, has obtained highest attention and the research of global numerous experts and scholars.Visit
Seek a kind of intelligent grid method for analyzing stability based on big data method, be one and there is learning value of crucial importance and reality
The research point of engineering application value.Huge pmu data gives the analysis of electrical network big data and brings data source.Seem from this part
The information obtaining needs in rich in natural resources is key point and the difficult point of electrical network big data analysis, that is, from magnanimity, various, real
When, electrical network state information excavating suitable electrical network decision analysis in the analysis of real electrical network big data most important.
Content of the invention
Present invention aims to the problems referred to above, there is provided a kind of grid stability based on electrical network pmu big data
Method of discrimination, by the statistical property of pmu historical data, real time data etc., in conjunction with the demand of electrical network, is carried out to stablizing of electrical network
Cognitive.
The object of the present invention is achieved like this:
A kind of grid stability method of discrimination based on electrical network pmu big data is it is characterised in that the method includes following step
Rapid:
1) it is modeled according to electrical network pmu data separate random matrix, including below step by step:
1.1) electrical network is divided into four kinds by the running status according to electrical network, is respectively as follows: that topological structure of electric is constant, electrical network is opened up
Flutter structure change, constant and electrical network the power supply source of power supply source of electrical network has increase and decrease；
1.2) observe and record four kinds of running statuses electrical network node at different levels pmu data；
1.3) from electric network swim equation, set up the pass between the observation of pmu data and operation of power networks state change
System, that is, the random matrix of electrical network pmu data represents；
2) electrical network pmu historical data is analyzed, including below step by step:
2.1) the pmu historical data of record is fifty-fifty divided into multiple time segment datas；
2.2) the pmu historical data of record is normalized；
2.3) calculate the eigenvalue distribution function of pmu historical data, then obtain the ginseng of the distribution bound of this function
Number, finally gives the upper and lower bound function of distribution of pmu historical data, and sets up the distribution bound figure of pmu historical data；
3) electrical network pmu real time data is analyzed, including below step by step:
3.1) record pmu real time data；
3.2) calculate the eigenvalue distribution function of pmu real time data, and set up the feature Distribution value of pmu real time data
Figure；
4) by the distribution bound figure of the eigenvalue scattergram of pmu real time data and pmu historical data on same interface
It is shown and compare；If the eigenvalue of pmu real time data falls between the distribution bound of pmu historical data, judge electrical network
For steady statue；Otherwise, then judge electrical network for abnormality.
Further, described step 4) in, the eigenvalue scattergram of described pmu real time data and the distribution of pmu historical data
Bound figure is shown by man machine interface.
The invention has the benefit that the method is the data (number such as voltage, electric current, power and phase angle using pmu collection
According to) carry out study and the differentiation of electric network state, therefore, the method does not rely on the topological structure of electrical network, is based entirely on pmu number
According to higher-dimension statistical property, thus applied widely, sane to spend high and safety reliable.
Brief description
Fig. 1 is the flow chart of the present invention.
When Fig. 2 is to be modeled using covariance matrix, the stable state diagram of operation of power networks.
When Fig. 3 is to be modeled using covariance matrix, the abnormal state diagram of operation of power networks.
When Fig. 4 is to be modeled using Eugene Wigner matrix, the stable state diagram of operation of power networks.
When Fig. 5 is to be modeled using Eugene Wigner matrix, the abnormal state diagram of operation of power networks.
Specific embodiment
With reference to specific embodiments and the drawings, the present invention is expanded on further.
As shown in figure 1, a kind of grid stability method of discrimination based on electrical network pmu big data, comprise the following steps:
1) it is modeled according to electrical network pmu data separate random matrix, power grid stability analysis are converted into random matrix
Problem analysis, including below step by step:
1.1) electrical network is divided into four kinds by the running status according to electrical network, is respectively as follows: that topological structure of electric is constant, electrical network is opened up
Flutter structure change, constant and electrical network the power supply source of power supply source of electrical network has increase and decrease；
1.2) observe and record four kinds of running statuses electrical network node at different levels pmu data；
1.3) from electric network swim equation, set up the pass between the observation of pmu data and operation of power networks state change
System, that is, the random matrix of electrical network pmu data represents；
2) electrical network pmu historical data is analyzed, including below step by step:
2.1) the pmu historical data of record is fifty-fifty divided into multiple time segment datas；
2.2) the pmu historical data of record is normalized, data will deduct the statistics of overall historical data
Average, then the variance divided by overall historical data；
2.3) calculate the eigenvalue distribution function of pmu historical data, then obtain the ginseng of the distribution bound of this function
Number, finally gives the upper and lower bound function of distribution of pmu historical data, and sets up the distribution bound figure of pmu historical data；
3) electrical network pmu real time data is analyzed, including below step by step:
3.1) record pmu real time data；
3.2) calculate the eigenvalue distribution function of pmu real time data, and set up the feature Distribution value of pmu real time data
Figure；
4) by the distribution bound figure of the eigenvalue scattergram of pmu real time data and pmu historical data on same interface
It is shown and compares, and observed and judge for convenience of electrical network operation management person, the eigenvalue of pmu real time data here
The distribution bound figure of scattergram and pmu historical data can be shown by man machine interface；If the feature of pmu real time data
Value falls between the distribution bound of pmu historical data, judges electrical network for steady statue, as shown in Figure 2 and Figure 4；Otherwise, then sentence
Power-off net is abnormality, as shown in Figure 3 and Figure 5.
Claims (2)
1. a kind of grid stability method of discrimination based on electrical network pmu big data is it is characterised in that the method includes following step
Rapid:
1) it is modeled according to electrical network pmu data separate random matrix, including below step by step:
1.1) electrical network is divided into four kinds by the running status according to electrical network, is respectively as follows: that topological structure of electric is constant, power network topology knot
Structure change, constant and electrical network the power supply source of power supply source of electrical network have increase and decrease；
1.2) observe and record four kinds of running statuses electrical network node at different levels pmu data；
1.3) from electric network swim equation, set up the relation between the observation of pmu data and operation of power networks state change, that is,
The random matrix of electrical network pmu data represents；
2) electrical network pmu historical data is analyzed, including below step by step:
2.1) the pmu historical data of record is fifty-fifty divided into multiple time segment datas；
2.2) the pmu historical data of record is normalized；
2.3) calculate the eigenvalue distribution function of pmu historical data, then obtain the parameter of the distribution bound of this function,
Obtain the upper and lower bound function of distribution of pmu historical data eventually, and set up the distribution bound figure of pmu historical data；
3) electrical network pmu real time data is analyzed, including below step by step:
3.1) record pmu real time data；
3.2) calculate the eigenvalue distribution function of pmu real time data, and set up the eigenvalue scattergram of pmu real time data；
4) the distribution bound figure of the eigenvalue scattergram of pmu real time data and pmu historical data is carried out on same interface
Show and compare；If the eigenvalue of pmu real time data falls between the distribution bound of pmu historical data, judge that electrical network is steady
Determine state；Otherwise, then judge electrical network for abnormality.
2. a kind of grid stability method of discrimination based on electrical network pmu big data according to claim 1, its feature exists
In described step 4) in, the distribution bound figure of the eigenvalue scattergram of described pmu real time data and pmu historical data passes through
Man machine interface is shown.
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Cited By (3)
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| CN107132454A (en) * | 2017-05-04 | 2017-09-05 | 国网上海市电力公司 | The abnormal quick determination method of power network based on random matrix spectral radius method |
| CN108053110A (en) * | 2017-12-11 | 2018-05-18 | 辽宁欣科电气股份有限公司 | A kind of transformer state inline diagnosis method based on PMU data |
| CN109193650A (en) * | 2018-10-26 | 2019-01-11 | 湖北航天技术研究院总体设计所 | A kind of power grid weak spot appraisal procedure based on higher-dimension Random Matrices Theory |
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| CN109193650A (en) * | 2018-10-26 | 2019-01-11 | 湖北航天技术研究院总体设计所 | A kind of power grid weak spot appraisal procedure based on higher-dimension Random Matrices Theory |
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