CN107133255A - A kind of bulk power grid full view safety defence method and system - Google Patents
A kind of bulk power grid full view safety defence method and system Download PDFInfo
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- CN107133255A CN107133255A CN201710153609.6A CN201710153609A CN107133255A CN 107133255 A CN107133255 A CN 107133255A CN 201710153609 A CN201710153609 A CN 201710153609A CN 107133255 A CN107133255 A CN 107133255A
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- G06F16/90—Details of database functions independent of the retrieved data types
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- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
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- 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
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Abstract
The invention provides a kind of bulk power grid full view safety defence method and system, the system includes physical layer, transport layer, computation layer and presentation layer；And the periodicity electric network data of collection is merged and transmitted by the system of defense, and transmission data are analyzed and stored, to carry out data mining to electric network data；According to the data mining to electric network data, the electric network data after being handled with the calculating of big data technology, and display data result of calculation.The technical scheme that the present invention is provided effectively improves electric power space-time big data intelligent excavating depth and utilizes range, to realize that global energy internet Initiative Defense provides solid technical support.
Description
Technical field
The invention belongs to scale grid line security monitoring and early warning field, in particular to a kind of bulk power grid full view safety is prevented
Imperial method and system.
Background technology
The uneven distribution of the energy, economic uncoordinated development and environmental problem are highlighted, following development mould of the energy
Formula will show the energy internet of renewable new energy technology and information Internet technology depth integration, realize the energy it is efficient,
Safety, economy and flexible development, meanwhile, energy internet will be to the development of electrician's subject, theoretical research and engineer applied band
Carry out huge opportunities and challenges.Under the fast-developing trend of regenerative resource high permeability and energy internet, power network also will be in
Now more complicated random, multi-source big data and multiple dimensioned dynamic characteristic, the undoubtedly real-time monitoring to bulk power grid are proposed more
High requirement.
Some area occur large area blackouts, expose it is existing with " modeling and simulating+forecast failure " be core
Safety on line system of defense operating mechanism, it is ageing in terms of the problems that exist, be mainly reflected in：Analogue system is near
Like actual physics system, sample space is limited, measured data utilization rate is low, for questionnaire one, Situation Awareness and pre-alerting ability
It is weak, can not meet scale grid line security requirement at ageing aspect.
From integrally, excavating depth and application range to bulk power grid wide area measurement information are reached far away based on monitor supervision platform
With the bulk power grids of wide area measurement data " real-time Accurate Analysis, wide area coordinate control and dynamic is autonomous " intelligent Defensive Target, because
This proposes more urgent requirement to bulk power grid real time execution Situation Assessment and intelligent control.
With regard to power grid security system of defense design to the meaning of power network safety operation, and power network safety operation skill
For art needs, it is desirable to provide a kind of power grid security system of defense, to improve the assessment to operation of power networks situation and monitoring.
The content of the invention
To meet existing power network safety operation monitoring and the demand assessed, big data is based on the invention provides one kind
The bulk power grid full view safety system of defense embodiment of technology.
On one side, the invention provides a kind of method of bulk power grid full view safety defence, it is theed improvement is that, the party
Method includes：
The electric network data gathered in advance is processed as to unified information format, electric network data and root after the processing is transmitted
Corresponding database is arrived according to data structure form storage；
The electric network data is calculated, the factor of the influence stabilization of power grids is extracted, power network space time correlation constraint mould is set up
Type；
The electric network data is excavated, power network is assessed using the Time-Space Kinetics characteristic and associate feature of electric network data
Operation situation, and the offer prevention and control strategy after there is Risk-warning；
The knowledge base of power network space-time data event behavior is built, power network anomalous event and early warning is excavated；
Visual presentation is carried out to above-mentioned data result of calculation.
Further, the electric network data includes：Grid simulation data, real-time steady-state load flow data, dynamic trajectory data
With power network external environment data.
Further, methods described further comprises：
Real-time the steady-state load flow data and dynamic trajectory data are carried out with Stream Processing, analysis catches the abnormal row of power network
To set up power network dynamic evaluation model with reference to historical data.
Further, it is described that the electric network data gathered in advance is processed as to unified information format, transmit after the processing
Electric network data, including：
The electric network data of periodicity collection is converted into unified information lattice by data cleansing, integrated, conversion and reduction
Formula；
Using increasing income, data transfer tool Sqoop extracts power network number from relevant database according to data structure form
According to, and the electric network data of extraction is passed into distributed system architecture Hadoop with ETL instrument Kettle softwares of increasing income；
Electric network data is uploaded to distributed post and subscribes to message system Kafka clusters.
Further, the power network dynamic evaluation model K is shown below：
Wherein,
The constraints of the power network dynamic evaluation model is shown below：
In formula, PGi：The active power output of i-th generating set；PGimin：The active power output lower limit of i-th generator；PGimax：
The active power output upper limit of i-th generator；QGi：I-th the idle of generating set is exerted oneself；QGimin：I-th generator it is idle
Exert oneself lower limit；QGimax：The idle upper limit of exerting oneself of i-th generator；PLi：The active power of i-th of load bus；PLimin：I-th
Individual load bus active power minimum value；PLimax：I-th of load bus active power maximum；QLi：I-th load bus
Reactive power；QLimin：The reactive power minimum value of i-th of load bus；QLimax：The reactive power of i-th of load bus is maximum
Value；All generator output summations；All load power summations；The voltage of each generator node,Each load
The voltage of node；Generating node current electric current sum；Each load bus electric current sum；Equivalent generating node electricity
Pressure；Equivalent load bus voltage；Power generation resistance；Load impedance；Take the conjugation of generated output；Take negative
The conjugation of lotus power.
Further, it is described that corresponding database is arrived according to data structure form storage, including：
By different types of electric network data combination data format and data use, full disk database, half internal memory are stored in
In database or all-memory database；
With Redis database purchase results of intermediate calculations；Calculated in real time with MySQL database storage and off-line calculation knot
Really.
Further, it is described that above-mentioned data result of calculation progress visual presentation is included：
Web visualization techniques are used, with instrument, pie chart or three-dimensional map mode display data result of calculation；
Map is scaled with the scalable vector graphicses SVG technologies for not changing pixel, with reference to node topology visual presentation number
According to result of calculation；
With computer graphics, image processing techniques, Multi-scale Represent of Spatial Data technology or map vector technology, carry out
Disturbing source is scanned to be shown with positioning, the division of disturbance domain, energy dynamics flowing and energy internet three-dimensional backbone network.
On the other hand, present invention also offers a kind of system of bulk power grid full view safety defence, the system includes：
Physical layer, transport layer, accumulation layer, computation layer and presentation layer, the computation layer include process layer and service layer；
Wherein, physical layer, for the electric network data gathered in advance to be processed as to unified information format；
Transport layer, for transmitting the electric network data after the processing to accumulation layer；
Accumulation layer, for arriving corresponding database according to data structure form storage；
Computation layer, for calculating the electric network data, extracts the factor of the influence stabilization of power grids, sets up power network space-time
Interconnection constraint model, is excavated to the electric network data, is commented using the Time-Space Kinetics characteristic and associate feature of electric network data
Estimate grid operation situation, and prevention and control strategy is provided after there is Risk-warning, build the knowledge of power network space-time data event behavior
Storehouse, excavates power network anomalous event and early warning；
Presentation layer, for carrying out visual presentation to above-mentioned data result of calculation.
Further, the accumulation layer is service PaaS platform, the service layer and presentation layer positioned at platform with process layer
It is service SaaS platforms positioned at software, the accumulation layer, process layer and service layer are service IaaS platforms institute using infrastructure
Virtual resources and physical equipment resource the processing electric network data of offer.
Further, the PaaS platform also includes default knowledge base, algorithms library and MySQL, Redis database.
With immediate prior art ratio, the technical scheme that the present invention is provided has the advantages that：
1st, the electric network data gathered in advance pretreatment is unified information format by the technical scheme that the present invention is provided, and is pressed
Preprocessed data is delivered to corresponding database according to specified format, and analyzes and stores the electric network data after processing；With including
Machine learning, figure are calculated and the data processing mode of stream calculation handles the electric network data stored；According to the storage after processing
Electric network data, power network is calculated with the big data technology of the Open Framework, programming model and computation model handled including distributed stream
Data, and show electric network data result of calculation；Realize power network panorama Situation Awareness key message it is directly perceived, real-time, quickly may be used
Depending on changing displaying, effectively improve electric power space-time big data intelligent excavating depth and utilize range, large-scale energy internet can be entered
Comprehensive, three-dimensional the security monitoring of row and accurate protection, to realize that global energy internet Initiative Defense provides reliable skill
Art is supported.
2nd, to define the bulk power grid full view safety system of defense based on big data technology general for the technical scheme that provides of the present invention
Considering functional framework, analyze system basic functions demand and have selected corresponding technical scheme, the detailed design big number of system
According to platform framework, deploy resource virtualizing (Resource Virtualization), Multi-source Information Fusion, distributed storage,
The excavation of space-time big data, panorama Situation Awareness, real-time stream calculation and the key technology that intuitively visualization etc. is closely related, can be effective
The polynary big data challenge under global energy internet environment is adapted to, with larger engineering application value and promotion prospect.
Brief description of the drawings
The major function Organization Chart for the bulk power grid full view safety system of defense that Fig. 1 provides for the present invention；
The platform framework schematic diagram for the bulk power grid full view safety system of defense that Fig. 2 provides for the present invention；
The platform visualization interface schematic diagram for the bulk power grid full view safety system of defense that Fig. 3 provides for the present invention.
Embodiment
Below with reference to Figure of description, the technical scheme that the present invention is provided is discussed in detail in the way of specific embodiment.
The essence of power network active safety defence is the high-effect processing and analysis to space-time big data, and information physical system leads to
Cross information, calculating to be organically blended and cooperated with depth with physical system, improve the intellectuality sense in real time of heavy construction system
Know and efficient Collaborative Control ability.Improve constantly and merged with internet, communication network even depth with power network intelligent level,
Power network will gradually be evolved into the complicated energy network with wide area collaboration, multidimensional collaboration and independent behaviour, so as to constitute energy system
The information and power system that system is blended with information physical system.At the same time, big data technology will be information and power systematic knowledge
Excavation system provides strong technical support.
The present invention bases oneself upon the global angle of power grid security defence, for the deficiency of existing power network, it is proposed that one kind is based on big number
According to the bulk power grid full view safety system of defense design of technology, further lifting power network self-organizing, adaptive, information Perception,
Integrated, shared, collaboration ability and intelligent Prevention-Security level, with stronger engineering application value.
To achieve the above object, the present invention provides a kind of brand-new safety defense system of utilization big data technique construction and put down
Platform, it is theed improvement is that, methods described comprises the following steps：
(1) gathers all kinds of emulation data of power network, real-time steady-state load flow or dynamic trajectory data and various by some cycles
The external environment data related to power network, above-mentioned multi-source heterogeneous data are merged.
The various electric network datas obtained in real time are converted into the system towards power network by data cleansing, integrated, conversion, reduction
One information format.With result collection system Flume gathered data daily records, it is responsible for from each node collection grid simulation number in real time
According to, real-time steady-state load flow, dynamic trajectory data, and external environment data with power network.
(2) to stream datas such as the grid simulation data of collection, real-time steady-state load flow and dynamic trajectory data and with electricity
The related external environment condition data of net are transmitted,.
ETL (Extract-Transform-Load) be for describe by data from source terminal through extraction (extract),
Change (transform), loading (load) to the process of destination, ETL processes：Using ETL instrument Kettle software pipes of increasing income
Manage the data from disparate databases and by specified format transmission.Data of increasing income transfer tool Sqoop is responsible for taking out from database
Access evidence, data are transmitted in Hadoop and relevant database.For the processing specification of data flow link, all data need system
One, which is uploaded to distributed post, subscribes to message system Kafka (Distributed Message Queue for being used for log processing) cluster, it is to avoid after
Hold the data processing problem of plurality of access modes.
(3) carries out economy, high scalability to the structuring of collection, semi-structured, unstructured data and real time data
Storage.There is provided with high fault-tolerant, reliable and throughput data storage method, to realize that extensive mass data storage is provided by force
Big base layer support.
With Redis database purchase results of intermediate calculations, with the real-time calculating of MySQL database storage, off-line calculation result.
In addition, data format, purposes etc. need to be combined for different types of data, in full disk database, half internal memory and full internal memory number
Preferentially stored according in storehouse；Data are effectively compressed, managed, the carrying cost of data is reduced, meanwhile, using data distribution formula
The technologies such as access control, Data Audit, data integrity validation, it is ensured that data safety, the storage and management of science.
(4) is handled the stream data of collection, real-time telemetry is analyzed, and power network abnormal behaviour is caught, with reference to history number
According to power network dynamic evaluation mould of the foundation based on temporal-spatial evolution incidence relation, multi-scale coupling relation and space time correlation constraints
Type.
Shown in the power network dynamic evaluation model such as following formula (1)：
Wherein,
And the constraints of power network dynamic evaluation model is shown below：
In formula, PGiFor the active power output of i-th generating set；PGiminFor the active power output lower limit of i-th generator；
PGimaxFor the active power output upper limit of i-th generator.QGiExerted oneself for i-th the idle of generating set；QGiminFor i-th generating
The idle lower limit of exerting oneself of machine；QGimaxFor the idle upper limit of exerting oneself of i-th generator.PLiFor the wattful power of i-th of load bus
Rate；PLiminFor i-th of load bus active power minimum value；PLimaxFor i-th of load bus active power maximum.QLiFor
The reactive power of i-th of load bus；QLiminFor the reactive power minimum value of i-th of load bus；QLimaxFor i-th of load
The reactive power maximum of node.For all generator output summations；For all load power summations.For each generator
The voltage of node,For the voltage of each load bus.For all generating node current electric current sums；For each load bus electricity
Flow sum.For equivalent generating node voltage；Equivalent load bus voltage.For power generation resistance；For load impedance.To take the conjugation of generated output；To take the conjugation of load power.
(5) carries out data mining to the electric network data of collection, and using lost motion mechanical characteristic and its associate feature are fast at that time
Speed assesses grid operation situation, provides prevention and control strategy in time after there is Risk-warning, it is ensured that the safety and economic operation of the whole network.
For the electric power space-time big data under various scenes, at the new data such as machine learning, figure calculating, stream calculation
Reason pattern, extracts the leading link and key factor of the influence stabilization of power grids, sets up a series of power network space time correlation restricted models.Structure
The knowledge base of power network space-time big data event behavior is built, is that the mode excavation, active forewarning, Real-time Decision of power network anomalous event are carried
For knowledge guaranteeing, operation of power networks Adaptive matching prevention and control system is improved.
(6) is calculated the electric power big data of acquisition process using big data technology, is related to space-time big data feature
The screening of amount is analyzed with stable calculation, the definite sign of multidimensional information and interaction fusion calculation analysis.It is related to uncertain factor
Space-time trend prediction, based on cluster, sorting technique disturbing influence domain identification, the sieve of panorama situation synthesis quantitative evaluation index
Choosing and polymerization etc..
In being calculated with big data technology the electric power big data of acquisition process, for real-time calculation and analysis, using with point
Cloth Computational frame distributed stream processing Open Framework Storm treatment technologies, its have high concurrent calculate disposal ability with
And powerful horizontal extension characteristic.In addition, the characteristics of technology also has incremental computations, it is sufficient to meet the defence of power network full view safety
System real-time calculation and analysis demand, ensures power network safety operation.
For off-line calculation, using MapReduce programming model treatment technologies, the technology has efficient TB, PB byte
DBMS disposal ability, set expandability is high, can dynamically increase memory node, it is sufficient to meet the off-line calculation of magnanimity electric power data
Analysis and demand.
For computationally intensive and high requirement of real-time module, handled using internal memory computing technique, the technology is adopted
The Open Framework Apache Spark handled with the distributed stream after improvement are as enforcement engine, with MapReduce programming models
Compare, without frequently I/O disk access, and use multithreading computation model, Start-up costs are small.
For the space-time big data of the different Run-time scenarios of power network, the stable situation for carrying out static power network, dynamic and transient state is real
When assess.Data are packaged, data sharing is realized, by data decoupler, data is solved and uses dumb problem.Power network is entered
The accurate diagnosis of row, prediction, lifting power network static state, transient state, dynamic analysis level, improve the panorama Situation Awareness energy of system of defense
Power.
(7) carries out data display to above-mentioned result of calculation.Shape is visualized using chart, instrument, map, two dimension, three-dimensional etc.
Formula, real-time, multidimensional, directly perceived, succinct displaying power network overall operation state and comprehensive Quantified Evaluation index.
Map is zoomed in and out without changing pixel, opened up with reference to national each node using scalable vector graphicses SVG technologies
Data are flutterred, energy is shown in the form of streaming.Using Web visualization techniques, the analysis result to electric power space-time big data is used
The methods such as instrument, pie chart, three-dimensional map carry out visual presentation directly perceived.Utilize computer graphics, image processing techniques, space
Data multi-scale expression technology and map vector technology, rapidly carry out disturbing source scanning and positioning, disturbance domain are divided, energy is moved
State flows and the displaying of global energy internet three-dimensional backbone network.
Embodiment
Fig. 1 major designs function framework of the bulk power grid full view safety system of defense based on big data technology, main work(
Can flow be：
(1) physical layer includes actual electric network grid structure and the external environment related to power network, and the present invention is gathered first
The electric network information of physical layer, external environment information, realize the collection and pretreatment to information, are that the follow-up safety for realizing power network is prevented
Imperial systems with data basis.
(2) transport layer, the storage and transmission of main responsible information, computation layer is transmitted to by the information after processing, screening,
Based data service is provided for computation layer.
(3) the big data technology that computation layer is mainly provided using the present invention, big data is carried out to the information after acquisition process
Analysis is with calculating.With reference to anticipation simulated fault collection and information-driven formula defense system, fuse information stream, energy stream, Business Stream are right
Bulk power grid carries out full view safety defence and calculates analysis.
(4) operation layer chief leading cadre machine is interacted, and using the Calculation results of computation layer, bulk power grid state is carried out real
When monitoring, power network is carried out safe early warning risk assessment and to provide safety guard measure according to power network virtual condition.
Function framework of the present invention is by brand-new electric power space-time big data comprehensive analysis with coordinating control cloud computing engine, prediction scheme
With responding the tactful cloud storehouse being combined, and electric network state monitoring and Risk-warning module composition, collect " monitoring+early warning+control "
In one, global energy internet different time dimension and the comprehensive of Spatial Dimension, three-dimensional Situation Awareness and accurate are realized
Control, it is ensured that power network is run in the way of more safe and reliable, real-time high-efficiency, wide area are coordinated.
Fig. 2 major designs platform framework of the bulk power grid full view safety system of defense based on big data technology, platform is real
Apply flow as follows：
(1) physical layer, specifically comprising extra-high voltage grid, intelligent grid, clean energy resource and external environment, physical layer is responsible for
The collection of information and preliminary pretreatment.
(2) transport layer, the transmission of main responsible data, ETL uses number of the Kettle tool management from disparate databases
According to simultaneously specified format transmission.Data of increasing income transfer tool Sqoop is responsible for carrying out the extraction of data from database, in distribution system
Data are transmitted in system architecture Hadoop and relevant database.For the processing specification of data flow link, all data need system
One, which is uploaded to distributed post, subscribes to message system Kafka clusters, it is to avoid the data processing problem of rear end plurality of access modes.
(3) accumulation layer, for using distributed storage to data, stores results of intermediate calculations with Redis, is deposited with MySQL
Storage is calculated in real time, off-line calculation result.In addition, data format, purposes etc. can be combined for different types of data, in full magnetic
Preferentially stored in disk database, half internal memory and all-memory database.Data are effectively compressed, managed, depositing for data is reduced
Store up cost.
(4) computation layer, the calculating of the main electric network data for being responsible for having stored after pretreatment；For entering to the electric network data
Row is calculated, and is extracted the factor of the influence stabilization of power grids, is set up power network space time correlation restricted model, the electric network data is dug
Pick, grid operation situation is assessed using the Time-Space Kinetics characteristic and associate feature of electric network data, and after there is Risk-warning
Prevention and control strategy is provided, the knowledge base of power network space-time data event behavior is built, power network anomalous event and early warning is excavated；
Computation layer includes process layer and service layer：
Process layer, offline batch processing, the streaming computing of data and the Spark for being substantially carried out data is calculated, wherein Spark
Calculate and be divided into internal memory and calculate (Spark Streaming), machine learning (Mlib), extemporaneous inquiry (Spark SQL), figure calculating
(GraphX) etc..
Service layer, it is main to be responsible for carrying out power network present situation comprehensive analysis, main bag according to big data platform result of calculation
Include：Static analysis, dynamic analysis, transient analysis, clustering, association analysis, spatio-temporal prediction, data retrieval, data interaction with
And data sharing etc..Existing main intelligent algorithm is mainly also provided including algorithms library, to carry out electricity net safety stable calculating；With knowing
Know storehouse, it is main to be responsible for carrying out electric network state comprehensive assessment according to big data result of calculation and provide corresponding decision-making.
(5) presentation layer, mainly from Stateful Inspection, the dynamic of three aspects of Risk-warning and defence policies respectively to power network
Topology, energy flow, Time-Space Kinetics are shown analysis.
Service layer and presentation layer composition SaaS platforms in the power grid security system of defense that the present invention is provided.
The accumulation layer, process layer and service layer are to service the virtual resources that IaaS platforms are provided using infrastructure
Electric network data is handled with physical equipment resource；IaaS podium levels, it is main to be responsible for providing high-performance physical equipment resource, virtualization money
Source.High-performance physical equipment resource mainly includes high-performance server, ultrahigh- density data storage device, basic running environment and network
Equipment.Resource virtualizing mainly includes virtualizing computing resource, storage resource, Internet resources.Pass through virtualization technology
Realize that software application is isolated with bottom hardware, it is contemplated that the demand in terms of performance, function, stability, reliability, can basis
Business characteristic, carries out targetedly depth for virtualization system and customizes, the demand for making it more meet service layer
And, SaaS platforms, PaaS platform, IaaS platforms and transport layer composition cloud information platform managing and control system.
Fig. 3 major designs the bulk power grid full view safety system of defense presentation layer framework based on big data technology, platform exhibition
Show that content is as follows：
(1) weak node of the energy in spatial flow, power network topology and power network of power network is showed from space-time three-dimensional perspective,
Weak node shows in luminous circle form.
(2) various states evaluation index is shown using instrument disk-form, different nargin models is represented with red, yellow, and green
Enclose.Different conditions evaluation index change curve is shown in the form of performance graph, is easy to operations staff to understand operation of power networks and becomes
Change situation.
(3) Asia, Europe, North America, South America, Oceania and African six big regions are shown in the form of D prism map
Stability margin index, can be carried out real-time to energy internet step by step from the whole world → intercontinental → country → provincial → at county level mode
Monitoring, defence.
It should be understood by those skilled in the art that, embodiments herein can be provided as method, system or computer program
Product.Therefore, the application can be using the reality in terms of complete hardware embodiment, complete software embodiment or combination software and hardware
Apply the form of example.Moreover, the application can be used in one or more computers for wherein including computer usable program code
The computer program production that usable storage medium is implemented on (including but is not limited to magnetic disk storage, CD-ROM, optical memory etc.)
The form of product.
The application is the flow with reference to method, equipment (system) and computer program product according to the embodiment of the present application
Figure and/or block diagram are described.It should be understood that can be by every first-class in computer program instructions implementation process figure and/or block diagram
Journey and/or the flow in square frame and flow chart and/or block diagram and/or the combination of square frame.These computer programs can be provided
The processor of all-purpose computer, special-purpose computer, Embedded Processor or other programmable data processing devices is instructed to produce
A raw machine so that produced by the instruction of computer or the computing device of other programmable data processing devices for real
The device for the function of being specified in present one flow of flow chart or one square frame of multiple flows and/or block diagram or multiple square frames.
These computer program instructions, which may be alternatively stored in, can guide computer or other programmable data processing devices with spy
Determine in the computer-readable memory that mode works so that the instruction being stored in the computer-readable memory, which is produced, to be included referring to
Make the manufacture of device, the command device realize in one flow of flow chart or multiple flows and/or one square frame of block diagram or
The function of being specified in multiple square frames.
These computer program instructions can be also loaded into computer or other programmable data processing devices so that in meter
Series of operation steps is performed on calculation machine or other programmable devices to produce computer implemented processing, thus in computer or
The instruction performed on other programmable devices is provided for realizing in one flow of flow chart or multiple flows and/or block diagram one
The step of function of being specified in individual square frame or multiple square frames.
The above embodiments are merely illustrative of the technical scheme of the present invention and are not intended to be limiting thereof, although with reference to above-described embodiment pair
The present invention is described in detail, and those of ordinary skill in the art can still enter to the embodiment of the present invention
Row modification or equivalent substitution, these any modifications or equivalent substitution without departing from spirit and scope of the invention, in application
Within pending claims of the invention.
Claims (10)
1. a kind of bulk power grid full view safety defence method, it is characterised in that this method includes：
The electric network data gathered in advance is processed as to unified information format, the electric network data after the processing is transmitted and according to number
Corresponding database is arrived according to structure type storage；
The electric network data is calculated, the factor of the influence stabilization of power grids is extracted, sets up power network space time correlation restricted model；
The electric network data is excavated, operation of power networks is assessed using the Time-Space Kinetics characteristic and associate feature of electric network data
Situation, and the offer prevention and control strategy after there is Risk-warning；
The knowledge base of power network space-time data event behavior is built, power network anomalous event and early warning is excavated；
Visual presentation is carried out to above-mentioned data result of calculation.
2. the method as described in claim 1, it is characterised in that the electric network data includes：Grid simulation data, real-time stable state
Flow data, dynamic trajectory data and power network external environment data.
3. method as claimed in claim 2, it is characterised in that methods described further comprises：
Real-time the steady-state load flow data and dynamic trajectory data are carried out with Stream Processing, analysis catches power network abnormal behaviour, knot
Close historical data and set up power network dynamic evaluation model.
4. the method as described in claim 1, it is characterised in that described that the electric network data gathered in advance is processed as to unified letter
Form is ceased, the electric network data after the processing is transmitted, including：
The electric network data of periodicity collection is converted into unified information format by data cleansing, integrated, conversion and reduction；
Using increasing income, data transfer tool Sqoop extracts electric network data from relevant database according to data structure form, and
The electric network data of extraction is passed into distributed system architecture Hadoop with ETL instrument Kettle softwares of increasing income；
Electric network data is uploaded to distributed post and subscribes to message system Kafka clusters.
5. method as claimed in claim 3, it is characterised in that the power network dynamic evaluation model K is shown below：
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Wherein,
The constraints of the power network dynamic evaluation model is shown below：
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In formula, PGi：The active power output of i-th generating set；PGimin：The active power output lower limit of i-th generator；PGimax：I-th
The active power output upper limit of platform generator；QGi：I-th the idle of generating set is exerted oneself；QGimin：I-th the idle of generator is exerted oneself
Lower limit；QGimax：The idle upper limit of exerting oneself of i-th generator；PLi：The active power of i-th of load bus；PLimin：I-th negative
Lotus node active power minimum value；PLimax：I-th of load bus active power maximum；QLi：I-th load bus it is idle
Power；QLimin：The reactive power minimum value of i-th of load bus；QLimax：The reactive power maximum of i-th of load bus；All generator output summations；All load power summations；The voltage of each generator node,Each load section
The voltage of point；Generating node current electric current sum；Each load bus electric current sum；Equivalent generating node voltage；Equivalent load bus voltage；Power generation resistance；Load impedance；Take the conjugation of generated output；Take load
The conjugation of power.
6. the method as described in claim 1, it is characterised in that described that corresponding data are arrived according to data structure form storage
Storehouse, including：
By different types of electric network data combination data format and data use, full disk database, half internal storage data are stored in
In storehouse or all-memory database；
With Redis database purchase results of intermediate calculations；Calculated in real time with MySQL database storage and off-line calculation result.
7. the method as described in claim 1, it is characterised in that described that visual presentation bag is carried out to above-mentioned data result of calculation
Include：
Web visualization techniques are used, with instrument, pie chart or three-dimensional map mode display data result of calculation；
Map is scaled with the scalable vector graphicses SVG technologies for not changing pixel, with reference to node topology visual presentation data meter
Calculate result；
With computer graphics, image processing techniques, Multi-scale Represent of Spatial Data technology or map vector technology, disturbed
Source is scanned to be shown with positioning, the division of disturbance domain, energy dynamics flowing and energy internet three-dimensional backbone network.
8. a kind of bulk power grid full view safety system of defense, it is characterised in that the system includes：Physical layer, transport layer, storage
Layer, computation layer and presentation layer, the computation layer include process layer and service layer；Wherein,
Physical layer, for the electric network data gathered in advance to be processed as to unified information format；
Transport layer, for transmitting the electric network data after the processing to accumulation layer；
Accumulation layer, for arriving corresponding database according to data structure form storage；
Computation layer, for calculating the electric network data, extracts the factor of the influence stabilization of power grids, sets up power network space time correlation
Restricted model, is excavated to the electric network data, and electricity is assessed using the Time-Space Kinetics characteristic and associate feature of electric network data
Network operation situation, and prevention and control strategy is provided after there is Risk-warning, the knowledge base of power network space-time data event behavior is built, is dug
Dig power network anomalous event and early warning；
Presentation layer, for carrying out visual presentation to above-mentioned data result of calculation.
9. system as claimed in claim 8, it is characterised in that the accumulation layer is that service PaaS is put down positioned at platform with process layer
Platform, the service layer is service SaaS platforms positioned at software with presentation layer, and the accumulation layer, process layer and service layer utilize basis
Facility is to service virtual resources and physical equipment resource processing electric network data that IaaS platforms are provided.
10. system as claimed in claim 9, it is characterised in that the PaaS platform also includes default knowledge base, algorithms library
And MySQL, Redis database.
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