CN109406943A - A kind of active distribution network monitoring method based on big data - Google Patents
A kind of active distribution network monitoring method based on big data Download PDFInfo
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- CN109406943A CN109406943A CN201811367923.5A CN201811367923A CN109406943A CN 109406943 A CN109406943 A CN 109406943A CN 201811367923 A CN201811367923 A CN 201811367923A CN 109406943 A CN109406943 A CN 109406943A
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/081—Locating faults in cables, transmission lines, or networks according to type of conductors
- G01R31/086—Locating faults in cables, transmission lines, or networks according to type of conductors in power transmission or distribution networks, i.e. with interconnected conductors
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
- G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
- G01R31/08—Locating faults in cables, transmission lines, or networks
- G01R31/088—Aspects of digital computing
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- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y04—INFORMATION OR COMMUNICATION TECHNOLOGIES HAVING AN IMPACT ON OTHER TECHNOLOGY AREAS
- Y04S—SYSTEMS INTEGRATING TECHNOLOGIES RELATED TO POWER NETWORK OPERATION, COMMUNICATION OR INFORMATION TECHNOLOGIES FOR IMPROVING THE ELECTRICAL POWER GENERATION, TRANSMISSION, DISTRIBUTION, MANAGEMENT OR USAGE, i.e. SMART GRIDS
- Y04S10/00—Systems supporting electrical power generation, transmission or distribution
- Y04S10/50—Systems or methods supporting the power network operation or management, involving a certain degree of interaction with the load-side end user applications
- Y04S10/52—Outage or fault management, e.g. fault detection or location
Abstract
The active distribution network monitoring method based on big data that the present invention provides a kind of specifically comprises the following steps: to determine that the multi-source complex data of the active distribution network containing distributed generation resource is integrated and amalgamation mode；Determine that the operation of the active distribution network containing distributed generation resource perceives multilayer dynamic indicator system；Determine the active distribution network Intellisense and diagnosis scheme driven based on big data；Determine the fault identification scheme of the active distribution network key composition driven based on big data；Determine that the active distribution network intelligent fault based on multisource data fusion searches for positioning method；It constructs the active distribution network operation perception driven based on big data and positions integrated application system with fault identification.The present invention is determined that active distribution network multi-source complex data is integrated and is perceived multilayer dynamic indicator system, Intellisense and diagnosis scheme, the fault identification scheme of crucial composition and intelligent fault search locating scheme with integration technology, operation based on big data technology.
Description
Technical field
The invention belongs to power network monitoring technical field, in particular to a kind of active distribution network monitoring side based on big data
Method.
Background technique
In terms of active distribution network operational monitoring research is concentrated mainly on electric energy quality monitoring.The operating status of active distribution network
Closely related with the access way and operating condition of power quality situation and distributed generation resource, the change of direction of tide can be to electric energy
Quality level produces bigger effect.So the electric energy quality monitoring to active distribution network is different from general power distribution network, in monitoring electricity
While energy quality status of implementation, it is also necessary to the consumption process and direction of tide of distributed generation resource are monitored, it is reasonable to formulate
Coordination control strategy mitigates power quality situation in the case where not influencing load electricity consumption.
It is also most important to the zone location of failure when active distribution network breaks down.For the DG's containing high permeability
The fault location of power distribution network has a large amount of correlative study at present.One kind more typical method is by DG and power grid company
Junction voltage and current measures, and observes its synchronism to determine whether failure has occurred.Another method is to be directed to
The improvement fault location strategy according to fault current information that overhead distributionnetwork proposes, using the cooperation of reclosing and DG off-grid,
Solve the fault-location problem of the overhead distributionnetwork containing DG.
The data type of active distribution network is various, and currently used method is to construct a set of unified number according to IEC61970
According to model, the information exchange and data sharing between all kinds of operation systems are realized.The data variation speed of active distribution network is fast, this
To the real time data processing ability of system, more stringent requirements are proposed, and some researches show that the SCADA system of normal operation is as received
It is delayed to monitoring data more than 50ms, that is, will lead to the control strategy of mistake, thus mass data must be carried out interior in short-term
Analysis, to support decision-making.The data volume of active distribution network is huge, and data volume is the decades of times of legacy system.Active distribution
The data value density of net is low, there is a problem of in equipment condition monitoring same, and most data collected is all just
Regular data, only minimal amount of abnormal data, and abnormal data is the important evidence of repair based on condition of component.It can additionally collect and include
The second-rate data of uncertain factors such as noise, shortage of data.So needing through diggers such as cluster, association, classification
Tool, extracts useful information from mass data.
To sum up, although domestic is to have certain research to active distribution network correlation operation characteristic, fault characteristic.But
Be for big data technology the data modeling of active distribution network, data correlation, data mining, in terms of research
Still need further to be expanded.Active distribution network operational monitoring, fault diagnosis and event of the research simultaneously based on big data technology
It is also particularly important to hinder area positioning technology.
Summary of the invention
The present invention determines integrated active distribution network multi-source complex data and integration technology, fortune based on big data technology
Row perception multilayer dynamic indicator system, Intellisense and diagnosis scheme, the fault identification scheme of crucial composition and intelligent fault are searched
Rope locating scheme.
The present invention is specially a kind of active distribution network monitoring method based on big data, and the active based on big data is matched
Power network monitoring method specifically comprises the following steps:
Step (1): the multi-source complex data of the determining active distribution network containing distributed generation resource integrates and amalgamation mode；
Step (2): determine that the operation of the active distribution network containing distributed generation resource perceives multilayer dynamic indicator system；
Step (3): the active distribution network Intellisense and diagnosis scheme driven based on big data is determined；
Step (4): the fault identification scheme of the active distribution network key composition driven based on big data is determined；
Step (5): determine that the active distribution network intelligent fault based on multisource data fusion searches for positioning method；
Step (6): the active distribution network operation perception and the integrated application of fault identification positioning driven based on big data is constructed
System.
Further, the step (1) determines that the multi-source complex data of the active distribution network containing distributed generation resource integrates and melts
Conjunction mode specifically comprises the following steps:
Step (11): active distribution network topological data, smart grid Dispatching Control System data, power distribution automation number are collected
According to, photovoltaic plant access data, meteorological data, electricity consumption acquisition data and dispatching log data；
Step (12): data are carried out with the analysis of attribute, and establishes suitable property index and classification；
Step (13): different to multi-source respectively by data assessment, data recombination, data cleansing, data pick-up, data filtering
Structure data are handled, and save as the format of data matrix；
Step (14): fusion and the Integrated Solution of the compound isomeric data of active distribution network multi-source are proposed according to data characteristics；
Step (15): the intelligent association model between different data sources is established.
Further, the step (2) determines that the operation of the active distribution network containing distributed generation resource perceives multilayer dynamic indicator
System specifically includes following content: establishing active distribution network operating status perception multilayer dynamic indicator system, including distributed electrical
Source health indicator, power supply quality index, active distribution network control class index.
Further, the step (3) determines the active distribution network Intellisense and diagnosis scheme driven based on big data
Specifically comprise the following steps:
Step (31): for the incomplete feature of active distribution network immediate data, research is based on associated data model of mind
Index system knowledge reasoning computing technique, establish active distribution network operation state overall performane；
Step (32): the real-time perception and diagnostic techniques that are able to reflect active distribution network key component units state are proposed；
Step (33): for the complete application scenarios of operation data, determine that the index system knowledge based on redundant data pushes away
Reason calculates correction technique, establishes the state aware of active distribution network containing new energy and diagnosis scheme of high reliability.
Further, the step (4) determines the fault identification of the active distribution network key composition driven based on big data
Scheme specifically comprises the following steps:
Step (41): utilizing big data analysis method, obtains distributed generation resource in active distribution network, wireline core composition is set
Standby fault message；
Step (42): using data mining technology between fault data correlation and characteristic quantity analyze, extract not
With the data characteristics of failure；
Step (43): calculating multidimensional diagnosis index, establishes the multidimensional diagnostic data base towards failure；
Step (44): based on database, the active distribution network of multidimensional diagnosis index feature comparison technology is determined the use of
Core component devices diagnose identification scheme.
Further, the step (5) determines that the active distribution network intelligent fault based on multisource data fusion searches for positioning
Mode specifically comprises the following steps:
Step (51): it based on active distribution network grid topology, according to fault characteristic, establishes and network topology section
The associated fault data matrix of point；
Step (52): it on the basis of fault data matrix, is formed using the method for data structure using fault data as base
The search tree of plinth, thus according to the data of search tree, it is theoretical based on multiterminal data difference, determine that fault zone intelligent search positions
Mode.
Further, step (6) building runs perception and fault identification based on the active distribution network that big data drives
Positioning integrated application system specifically comprises the following steps:
Step (61): based on the initial data of active distribution network, analysis means is handled by big data, are established actively
The compound heterogeneous data table of power distribution network multi-source；
Step (62): being based on active distribution network big data analysis, constructs the active distribution network operation driven based on big data
Perception positions integrated application system with fault identification.
Specific embodiment
A kind of specific embodiment of the active distribution network monitoring method based on big data of the present invention is done below and is explained in detail
It states.
The present invention is based on the active distribution network monitoring methods of big data to specifically comprise the following steps:
Step (1): the multi-source complex data of the determining active distribution network containing distributed generation resource integrates and amalgamation mode；
Step (2): determine that the operation of the active distribution network containing distributed generation resource perceives multilayer dynamic indicator system；
Step (3): the active distribution network Intellisense and diagnosis scheme driven based on big data is determined；
Step (4): the fault identification scheme of the active distribution network key composition driven based on big data is determined；
Step (5): determine that the active distribution network intelligent fault based on multisource data fusion searches for positioning method；
Step (6): the active distribution network operation perception and the integrated application of fault identification positioning driven based on big data is constructed
System.
Further, the step (1) determines that the multi-source complex data of the active distribution network containing distributed generation resource integrates and melts
Conjunction mode specifically comprises the following steps:
Step (11): active distribution network topological data, smart grid Dispatching Control System data, power distribution automation number are collected
According to, photovoltaic plant access data, meteorological data, electricity consumption acquisition data and dispatching log data；
Step (12): data are carried out with the analysis of attribute, and establishes suitable property index and classification；
Step (13): different to multi-source respectively by data assessment, data recombination, data cleansing, data pick-up, data filtering
Structure data are handled, and save as the format of data matrix；
Step (14): fusion and the Integrated Solution of the compound isomeric data of active distribution network multi-source are proposed according to data characteristics；
Step (15): the intelligent association model between different data sources is established.
Further, the step (2) determines that the operation of the active distribution network containing distributed generation resource perceives multilayer dynamic indicator
System specifically includes following content: establishing active distribution network operating status perception multilayer dynamic indicator system, including distributed electrical
Source health indicator, power supply quality index, active distribution network control class index.
Further, the step (3) determines the active distribution network Intellisense and diagnosis scheme driven based on big data
Specifically comprise the following steps:
Step (31): for the incomplete feature of active distribution network immediate data, research is based on associated data model of mind
Index system knowledge reasoning computing technique, establish active distribution network operation state overall performane；
Step (32): the real-time perception and diagnostic techniques that are able to reflect active distribution network key component units state are proposed；
Step (33): for the complete application scenarios of operation data, determine that the index system knowledge based on redundant data pushes away
Reason calculates correction technique, establishes the state aware of active distribution network containing new energy and diagnosis scheme of high reliability.
Further, the step (4) determines the fault identification of the active distribution network key composition driven based on big data
Scheme specifically comprises the following steps:
Step (41): utilizing big data analysis method, obtains distributed generation resource in active distribution network, wireline core composition is set
Standby fault message；
Step (42): using data mining technology between fault data correlation and characteristic quantity analyze, extract not
With the data characteristics of failure；
Step (43): calculating multidimensional diagnosis index, establishes the multidimensional diagnostic data base towards failure；
Step (44): based on database, the active distribution network of multidimensional diagnosis index feature comparison technology is determined the use of
Core component devices diagnose identification scheme.
Further, the step (5) determines that the active distribution network intelligent fault based on multisource data fusion searches for positioning
Mode specifically comprises the following steps:
Step (51): it based on active distribution network grid topology, according to fault characteristic, establishes and network topology section
The associated fault data matrix of point；
Step (52): it on the basis of fault data matrix, is formed using the method for data structure using fault data as base
The search tree of plinth, thus according to the data of search tree, it is theoretical based on multiterminal data difference, determine that fault zone intelligent search positions
Mode.
Further, step (6) building runs perception and fault identification based on the active distribution network that big data drives
Positioning integrated application system specifically comprises the following steps:
Step (61): based on the initial data of active distribution network, analysis means is handled by big data, are established actively
The compound heterogeneous data table of power distribution network multi-source；
Step (62): being based on active distribution network big data analysis, constructs the active distribution network operation driven based on big data
Perception positions integrated application system with fault identification.
Finally it should be noted that only illustrating technical solution of the present invention rather than its limitations in conjunction with above-described embodiment.Institute
The those of ordinary skill in category field is it is to be understood that those skilled in the art can repair a specific embodiment of the invention
Change or equivalent replacement, but these modifications or change are being applied among pending claims.
Claims (7)
1. a kind of active distribution network monitoring method based on big data, which is characterized in that the active distribution based on big data
Net monitoring method specifically comprises the following steps:
Step (1): the multi-source complex data of the determining active distribution network containing distributed generation resource integrates and amalgamation mode；
Step (2): determine that the operation of the active distribution network containing distributed generation resource perceives multilayer dynamic indicator system；
Step (3): the active distribution network Intellisense and diagnosis scheme driven based on big data is determined；
Step (4): the fault identification scheme of the active distribution network key composition driven based on big data is determined；
Step (5): determine that the active distribution network intelligent fault based on multisource data fusion searches for positioning method；
Step (6): it constructs the active distribution network operation perception driven based on big data and positions integrated application system with fault identification.
2. a kind of active distribution network monitoring method based on big data according to claim 1, which is characterized in that the step
Suddenly (1) determines that the multi-source complex data of the active distribution network containing distributed generation resource is integrated and specifically comprises the following steps: with amalgamation mode
Step (11): collect active distribution network topological data, smart grid Dispatching Control System data, power distribution automation data,
Photovoltaic plant accesses data, meteorological data, electricity consumption acquisition data and dispatching log data；
Step (12): data are carried out with the analysis of attribute, and establishes suitable property index and classification；
Step (13): by data assessment, data recombination, data cleansing, data pick-up, data filtering respectively to multi-source heterogeneous number
According to being handled, and save as the format of data matrix；
Step (14): fusion and the Integrated Solution of the compound isomeric data of active distribution network multi-source are proposed according to data characteristics；
Step (15): the intelligent association model between different data sources is established.
3. a kind of active distribution network monitoring method based on big data according to claim 1, which is characterized in that the step
Suddenly (2) determine that the operation perception multilayer dynamic indicator system of the active distribution network containing distributed generation resource specifically includes following content: building
Vertical active distribution network operating status perceives multilayer dynamic indicator system, including distributed generation resource health indicator, power supply quality index,
Active distribution network controls class index.
4. a kind of active distribution network monitoring method based on big data according to claim 1, which is characterized in that the step
Suddenly (3) determination is specifically comprised the following steps: based on the active distribution network Intellisense that big data drives with diagnosis scheme
Step (31): for the incomplete feature of active distribution network immediate data, the finger based on associated data model of mind is studied
Mark system knowledge reasoning computing technique establishes active distribution network operation state overall performane；
Step (32): the real-time perception and diagnostic techniques that are able to reflect active distribution network key component units state are proposed；
Step (33): it for the complete application scenarios of operation data, determines based on the index system knowledge reasoning of redundant data
Correction technique is calculated, the state aware of active distribution network containing new energy and diagnosis scheme of high reliability are established.
5. a kind of active distribution network monitoring method based on big data according to claim 1, which is characterized in that the step
Suddenly (4) determine that the fault identification scheme of the active distribution network key composition driven based on big data is specifically comprised the following steps:
Step (41): utilizing big data analysis method, obtains distributed generation resource, wireline core component devices in active distribution network
Fault message；
Step (42): using data mining technology between fault data correlation and characteristic quantity analyze, extract it is different therefore
The data characteristics of barrier；
Step (43): calculating multidimensional diagnosis index, establishes the multidimensional diagnostic data base towards failure；
Step (44): based on database, the active distribution network core of multidimensional diagnosis index feature comparison technology is determined the use of
Component devices diagnose identification scheme.
6. a kind of active distribution network monitoring method based on big data according to claim 1, which is characterized in that the step
Suddenly (5) determine that the active distribution network intelligent fault search positioning method based on multisource data fusion specifically comprises the following steps:
Step (51): it based on active distribution network grid topology, according to fault characteristic, establishes and is closed with network topology node
The fault data matrix of connection；
Step (52): it on the basis of fault data matrix, is formed based on fault data using the method for data structure
Search tree, thus according to the data of search tree, it is theoretical based on multiterminal data difference, determine fault zone intelligent search positioning side
Formula.
7. a kind of active distribution network monitoring method based on big data according to claim 1, which is characterized in that the step
Suddenly (6) building is specifically included based on the active distribution network operation perception that big data drives with fault identification positioning integrated application system
Following steps:
Step (61): based on the initial data of active distribution network, analysis means is handled by big data, establish active distribution
The compound heterogeneous data table of net multi-source；
Step (62): being based on active distribution network big data analysis, constructs the active distribution network operation perception driven based on big data
Integrated application system is positioned with fault identification.
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Application publication date: 20190301 |