CN112381363A - Intelligent navigation method and system for power grid accident handling - Google Patents
Intelligent navigation method and system for power grid accident handling Download PDFInfo
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- G06Q10/063—Operations research, analysis or management
- G06Q10/0635—Risk analysis of enterprise or organisation activities
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/21—Design, administration or maintenance of databases
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
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- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/24—Querying
- G06F16/245—Query processing
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- G06F16/2465—Query processing support for facilitating data mining operations in structured databases
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- G—PHYSICS
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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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- G06—COMPUTING; CALCULATING OR COUNTING
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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
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- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
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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
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- 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
Abstract
The invention discloses an intelligent navigation method for power grid accident handling, which comprises the following steps: carrying out online fault diagnosis on a power grid accident, and identifying an online fault event of the power grid accident; acquiring online external environment information, and generating online risk early warning of the online fault event according to the online external environment information; integrating the online risk early warning by taking the online fault event as an index to form an online auxiliary decision of the online fault event; and establishing a visual framework of the online aid decision. In the embodiment of the invention, by adopting the intelligent navigation method and the system for processing the power grid accidents, an optimal power grid accident processing scheme can be found by automatically combining with the external environment, and a power grid dispatcher can be guided to process the power grid accidents, so that the intelligent navigation method and the system have good practicability.
Description
Technical Field
The invention relates to the technical field of power grids, in particular to an intelligent navigation method and system for processing power grid accidents.
Background
With the increasingly complex power grid architecture, when a power grid accident occurs and needs to be processed, due to the diversification of the power grid accident, the processing plans of the power grid accident are different, and even if the same fault occurs, the processing steps are also different under different external environments, so that a power grid dispatcher is influenced by the external environments when processing the power grid accident, and the finally adopted power grid accident processing method is not necessarily the optimal power grid accident processing scheme.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides the intelligent navigation method and the system for processing the power grid accidents.
Correspondingly, the embodiment of the invention provides an intelligent navigation method for processing power grid accidents, which comprises the following steps:
carrying out online fault diagnosis on a power grid accident, and identifying an online fault event of the power grid accident;
acquiring online external environment information, and generating online risk early warning of the online fault event according to the online external environment information;
integrating the online risk early warning by taking the online fault event as an index to form an online auxiliary decision of the online fault event;
and establishing a visual framework of the online aid decision.
In an optional embodiment, the intelligent navigation method for handling the power grid accident further includes:
and establishing a heterogeneous database.
In an optional embodiment, the intelligent navigation method for handling the power grid accident further includes:
the method comprises the steps of collecting steady-state data, dynamic data and transient-state data of power grid operation, and storing the steady-state data, the dynamic data and the transient-state data in the heterogeneous database.
In an optional embodiment, the online fault diagnosis of the power grid accident and the identification of the online fault event of the power grid accident include:
retrieving the steady state data, the dynamic data, and the transient data from the heterogeneous database;
and carrying out online fault diagnosis on the power grid accident by using the steady-state data, the dynamic data and the transient data, and identifying an online fault event of the power grid accident.
In an optional embodiment, the intelligent navigation method for handling the power grid accident further includes:
and analyzing and refining the incidence relation between the historical fault events of the power grid and the historical external environment information through a data mining technology, and storing the incidence relation in the heterogeneous database.
In an optional embodiment, the obtaining online external environment information and generating an online risk early warning of the online fault event according to the online external environment information includes:
acquiring online external environment information through an online monitoring system;
and calling the incidence relation from the heterogeneous database, and generating the risk early warning of the online fault event according to the online external environment information by taking the incidence relation as a basis.
In an optional embodiment, the intelligent navigation method for handling the power grid accident further includes:
and establishing an online assistant decision large model based on a dynamic verification method and a soft handover technology, and storing the online assistant decision large model in the heterogeneous database.
In an optional embodiment, the intelligent navigation method for handling the power grid accident further includes:
establishing a large model management mechanism for distributed maintenance and real-time sharing of the whole network, and storing the large model management mechanism in the heterogeneous database;
and performing model management on the online assistant decision-making large model in the heterogeneous database by using the large model management mechanism.
In an optional embodiment, the integrating the online risk early warning by using the online failure event as an index to form an online assistant decision of the online failure event includes:
calling the online assistant decision large model from the heterogeneous database;
and integrating the online risk early warning into the online decision-making assisting large model by taking the online fault event as an index of the online decision-making assisting large model to form an online decision-making assisting of the online fault event.
In addition, an embodiment of the present invention provides an intelligent navigation system for handling a power grid accident, where the intelligent navigation system for handling a power grid accident includes:
a fault event identification module: the system comprises a power grid fault diagnosis module, a power grid fault diagnosis module and a power grid fault diagnosis module, wherein the power grid fault diagnosis module is used for carrying out online fault diagnosis on a power grid fault and identifying an online fault event of the power grid fault;
a risk early warning generation module: the online risk early warning system is used for acquiring online external environment information and generating an online risk early warning of the online fault event according to the online external environment information;
an assistant decision forming module: the online risk early warning is integrated by taking the online fault event as an index to form an online auxiliary decision of the online fault event;
an assistant decision visualization module: a visualization framework for establishing the online assistant decision.
The embodiment of the invention provides an intelligent navigation method and an intelligent navigation system for processing power grid accidents.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a schematic flow chart of an intelligent navigation method for handling a power grid accident in the embodiment of the invention;
FIG. 2 is a supplementary flowchart of the intelligent navigation method for handling the power grid accident in the embodiment of the present invention;
FIG. 3 is a flowchart illustrating a detailed process of S11 according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a detailed process of S12 according to an embodiment of the present invention;
FIG. 5 is a flowchart illustrating the detailed process of S13 according to an embodiment of the present invention;
fig. 6 is a schematic composition diagram of the intelligent navigation system for handling the power grid accident in the embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
FIG. 1 is a schematic flow chart of an intelligent navigation method for processing a power grid accident in the embodiment of the invention.
The embodiment of the invention provides an intelligent navigation method for processing power grid accidents, which comprises the following steps:
s11: carrying out online fault diagnosis on a power grid accident, and identifying an online fault event of the power grid accident;
after a power grid accident occurs to a power grid, carrying out online fault diagnosis on the power grid accident, and identifying an online fault event corresponding to the power grid accident.
S12: acquiring online external environment information, and generating online risk early warning of the online fault event according to the online external environment information;
in the embodiment of the invention, online external environment information needs to be acquired, the influence of the online external environment information on power grid accident handling is analyzed, and online risk early warning of the online fault event is generated, namely early warning information of the external environment in the power grid accident handling process is given, and the early warning information is avoided as much as possible in the power grid accident handling.
S13: integrating the online risk early warning by taking the online fault event as an index to form an online auxiliary decision of the online fault event;
in the embodiment of the invention, the online fault event is taken as an index, the online risk early warning is integrated, and the online auxiliary decision of the online fault event is formed, namely, in the power grid accident processing, the optimal power grid accident processing scheme can be found by automatically combining with the external environment.
The optimal power grid accident handling scheme can be found by automatically combining with the external environment, a power grid dispatcher can be guided to handle the power grid accident, and the method has good practicability.
S14: establishing a visual framework of the online aid decision;
in the embodiment of the invention, a visual framework of the online assistant decision is established, so that the online assistant decision is more visual and visible, and a power grid dispatcher is more conveniently guided to process power grid accidents.
Fig. 2 is a supplementary flowchart of the intelligent navigation method for handling the power grid accident in the embodiment of the present invention.
In an embodiment of the present invention, the intelligent navigation method for processing the power grid accident further includes:
s15: establishing a heterogeneous database;
with the expansion of the scale of a power grid and the multisource of operation data, especially the uploading of a large amount of high-frequency PMU real-time data, the conventional storage scheme based on a relational database is difficult to adapt to the development requirement of the power grid, and therefore a heterogeneous database combining the relational database and a dynamic information database is required to be adopted for unified management and service of the data. The relational database is suitable for describing data which does not change or slowly changes and has a mutual correlation relationship, so that the relational database is adopted for storing the model, the alarm information and the large field information of the power system, and the characteristic of high-efficiency real-time storage of the dynamic information database can be fully exerted for data which changes rapidly along with time, such as PMU dynamic data of 25 frames (or more) per second.
In a heterogeneous database environment, mass power information data provides unified, standard and transparent data access service to the outside through a virtual data access middleware. The application program does not need to care about the information such as the storage organization mode and the storage position of the data by using the middleware. The EMS system, the WAMS system and other application systems can transparently access mass power information by embedding virtual data access middleware into the application support platform, so that the requirements of the EMS system on high capacity, high reliability and quick response are met, and the application complexity is simplified.
In an embodiment of the present invention, the intelligent navigation method for processing the power grid accident further includes:
s16: acquiring steady-state data, dynamic data and transient-state data of power grid operation, and storing the steady-state data, the dynamic data and the transient-state data in the heterogeneous database;
the power grid operation data can be divided into three parts of a steady state, a dynamic state and a transient state according to time scales, the data with different time scales can be used for reflecting different characteristics of power grid operation, particularly in the power grid accident processing process, the three-state data is required to be comprehensively utilized for analysis, and a power grid dispatcher is assisted to carry out power grid accident processing, so that the steady state data, the dynamic data and the transient state data of the power grid operation need to be collected, the steady state data, the dynamic data and the transient state data are stored in the heterogeneous database, a unified centralized storage management platform of the three-state data is established in the heterogeneous database, and a data basis is provided for power grid accident processing auxiliary decision making.
The traditional three-state data storage management platform focuses on the collection of various types of data of a power grid, and lacks a unified information query service facing power grid disturbance, so a disturbance-oriented three-state data centralized management platform based on unified time needs to be established in the heterogeneous database, specifically, when the power grid disturbance occurs, steady-state data (state estimation data, switch deflection, protection action signals and the like), dynamic data (PMU real-time dynamic data and offline dynamic data files) and transient data (fault recording data) before and after the power grid disturbance are automatically extracted by taking the power grid disturbance as an index to form multi-state recording data related to the power grid disturbance, on one hand, a power grid dispatcher can inquire the data, on the other hand, a basic data source can be provided for applications such as accident inversion and model parameter checking, and the problems that manual data analysis, data analysis and data analysis of the dispatching operator are needed when the conventional power grid disturbance occurs are avoided, The complex process of arrangement greatly improves the production efficiency of power grid dispatching operation.
Fig. 3 is a schematic diagram of a specific flow of S11 in the embodiment of the present invention.
In an embodiment of the present invention, the performing online fault diagnosis on a power grid accident, and identifying an online fault event of the power grid accident includes:
s111: retrieving the steady state data, the dynamic data, and the transient data from the heterogeneous database;
s112: performing online fault diagnosis on the power grid accident by using the steady-state data, the dynamic data and the transient data, and identifying an online fault event of the power grid accident;
the online fault diagnosis is a key link of auxiliary decision-making for power grid accident treatment, and requires that a rapid and accurate alarm can be given when a power grid system really fails to remind a dispatching power grid of the failure and the exact position of the failure, so as to provide decision support for dispatching and performing fault treatment.
The three indexes of correctness, instantaneity and comprehensiveness are required to be considered in the design of the online fault diagnosis of the power grid. The correctness is that false alarm is not given under the condition that the power grid normally operates, and the alarm is not missed when the power grid really fails; the real-time property means that alarm information can be sent out at the first time when the power grid fails; the comprehensiveness mainly refers to the information on the granularity of the diagnosis result, including fault time, fault equipment, fault phase, coincidence condition, fault distance measurement, actually-measured short-circuit current and the like.
The method is limited by the limit of the development level of dispatching automation, and in the past, the single data source is mostly adopted for online fault diagnosis, so that the three aspects of correctness, instantaneity and comprehensiveness are difficult to balance, and the practical level of online fault diagnosis software is not high; with the development of computer and communication technology, the dispatching automation system makes remarkable progress, realizes the collection and uploading of steady, dynamic and transient data, and provides a foundation for researching on-line fault diagnosis based on comprehensive information.
The tri-state data describes characteristic information of the power grid fault in different time scales, and the information is redundant and supplemented with each other and is the most valuable data source for online fault diagnosis; specifically, the sampling frequency of transient data (namely fault recording files) is highest, generally not lower than 4800 points/s, the original waveforms of voltage and current can be completely recorded when the power grid fails, but the uploading speed is slower, generally in the order of min; the sampling frequency of dynamic data (namely voltage and current phasor data acquired by a PMU device) is second to that of transient data, generally not lower than 25 frames/s, and the dynamic data can record voltage and current mutation information during power grid faults and can be uploaded in real time; the sampling frequency of steady state data (namely information collected by the RTU device) is the lowest, the data are updated for 1 time in 4 to 5 seconds under the general condition, only switch displacement and protection action signals can be recorded, and meanwhile, the conditions of real-time uploading are met, but the change condition of the electric quantity when the power grid fails cannot be reflected. Therefore, in the aspect of correctness, the misjudgment and the missed judgment caused by unreliable data can be remarkably reduced through the information comprehensive criterion of the state quantity (switch deflection, protection action signals and the like) and the electric quantity (sudden change of voltage, current and the like); in the aspect of real-time performance, the characteristics of real-time uploading of steady-state data and dynamic data are fully utilized, the two types of data are preferentially utilized to carry out primary judgment on faults, and detailed analysis on the faults is carried out after transient data are uploaded; in the aspect of comprehensiveness, fault equipment, phase difference and coincidence conditions are preliminarily judged by utilizing the steady-state data and the dynamic data, and fault distance measurement and actually-measured short-circuit current calculation are further carried out by combining the transient data.
Through the cooperative processing of the tri-state data, the online fault diagnosis is unified in three aspects of correctness, instantaneity and comprehensiveness, the practical level of the online fault diagnosis is improved, and technical support is provided for the dispatching to quickly master the fault condition of the power grid.
In an embodiment of the present invention, the intelligent navigation method for processing the power grid accident further includes:
s17: analyzing and refining the incidence relation between the historical fault events of the power grid and the historical external environment information through a data mining technology, and storing the incidence relation in the heterogeneous database;
and acquiring historical fault events and historical external environment information through a data mining technology, analyzing and refining the incidence relation between the historical fault events and the historical external environment information of the power grid, and storing the incidence relation in the heterogeneous database.
Fig. 4 is a schematic diagram of a specific flow of S12 in the embodiment of the present invention.
In the embodiment of the present invention, the obtaining online external environment information and generating an online risk early warning of the online fault event according to the online external environment information includes:
s121: acquiring online external environment information through an online monitoring system;
s122: and calling the incidence relation from the heterogeneous database, and generating the risk early warning of the online fault event according to the online external environment information by taking the incidence relation as a basis.
In an embodiment of the present invention, the intelligent navigation method for processing the power grid accident further includes:
s18: and establishing an online assistant decision large model based on a dynamic verification method and a soft handover technology, and storing the online assistant decision large model in the heterogeneous database.
In the embodiment of the invention, an online assistant decision large model is established to carry out online assistant decision.
The reliability of modeling is improved through model dynamic verification and a soft switching online technology, and the impact of the model on an online operation system is reduced; the conventional power grid modeling of a real-time system has two methods, namely an online method and an offline method, the online modeling is convenient and simple, but the correctness of a model cannot be verified, so that the reliability of the system is influenced; however, in the offline modeling, only offline static verification is supported at present, an offline dynamic verification technology is lacked, only simple checking can be performed on contents such as connection relation, parameter reasonability and the like, and the correctness of the model cannot be comprehensively verified, so that a dynamic verification method is adopted in the modeling process, namely, in addition to performing static verification on information such as equipment parameters, connection relation, naming standards and the like, real-time section data is copied under a model verification environment, and state estimation software is utilized to verify the updated data, judge whether state estimation is converged, judge whether a calculation result is reasonable and the like.
Meanwhile, the conventional model online casting only has hard switching, namely, the mode of directly emptying and rewriting the model information of the online system is adopted in the hard switching, the model information is lack of a protection and control mechanism in the online casting process, so that the online system generates real-time data jumping in the switching process, and the soft switching technology adopts the mode of incrementally updating the model information of the online system, so that the model information protection and control mechanism is provided, the undisturbed online casting can be realized, and the data continuity of the online system is ensured.
In an embodiment of the present invention, the intelligent navigation method for processing the power grid accident further includes:
s191: establishing a large model management mechanism for distributed maintenance and real-time sharing of the whole network, and storing the large model management mechanism in the heterogeneous database;
s192: and performing model management on the online assistant decision-making large model in the heterogeneous database by using the large model management mechanism.
The method is characterized in that the construction of complete large model information among scheduling systems is the primary work of model management, the splicing of the traditional scheduling automation system models is complex in process, needs manual intervention, is poor in real-time performance and is difficult to be synchronized immediately, and on the other hand, splicing data are incomplete and cannot describe necessary information of system operation such as formulas, hang tags and the like, so that a model management mechanism of distributed maintenance and whole network immediate sharing needs to be established. The mode not only follows the principle of maintaining the model according to the scheduling jurisdiction range, but also has simple realization mode, ensures the convenience, reliability and instantaneity of the maintenance of the power grid model, and further realizes the timely synchronization and online mutual backup of the model.
Fig. 5 is a schematic diagram of a specific flow of S13 in the embodiment of the present invention.
In this embodiment of the present invention, the integrating the online risk early warning by using the online failure event as an index to form an online auxiliary decision of the online failure event includes:
s131: calling the online assistant decision large model from the heterogeneous database;
s132: and integrating the online risk early warning into the online decision-making assisting large model by taking the online fault event as an index of the online decision-making assisting large model to form an online decision-making assisting of the online fault event.
Fig. 6 is a schematic composition diagram of the intelligent navigation system for handling the power grid accident in the embodiment of the invention.
In addition, an embodiment of the present invention further provides an intelligent navigation system for handling a power grid accident, where the intelligent navigation system for handling a power grid accident includes:
a fault event identification module: the system comprises a power grid fault diagnosis module, a power grid fault diagnosis module and a power grid fault diagnosis module, wherein the power grid fault diagnosis module is used for carrying out online fault diagnosis on a power grid fault and identifying an online fault event of the power grid fault;
a risk early warning generation module: the online risk early warning system is used for acquiring online external environment information and generating an online risk early warning of the online fault event according to the online external environment information;
an assistant decision forming module: the online risk early warning is integrated by taking the online fault event as an index to form an online auxiliary decision of the online fault event;
an assistant decision visualization module: a visualization framework for establishing the online assistant decision.
The embodiment of the invention provides an intelligent navigation method and an intelligent navigation system for processing power grid accidents.
Those skilled in the art will appreciate that all or part of the steps in the methods of the above embodiments may be implemented by associated hardware instructed by a program, which may be stored in a computer-readable storage medium, and the storage medium may include: a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic or optical disk, or the like.
In addition, the above detailed description is given to the intelligent navigation method and system for processing the power grid accident, and a specific example is adopted herein to explain the principle and implementation manner of the present invention, and the description of the above embodiment is only used to help understanding the method and core idea of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, there may be variations in the specific embodiments and the application scope, and in summary, the content of the present specification should not be construed as a limitation to the present invention.
Claims (10)
1. The intelligent navigation method for processing the power grid accident is characterized by comprising the following steps of:
carrying out online fault diagnosis on a power grid accident, and identifying an online fault event of the power grid accident;
acquiring online external environment information, and generating online risk early warning of the online fault event according to the online external environment information;
integrating the online risk early warning by taking the online fault event as an index to form an online auxiliary decision of the online fault event;
and establishing a visual framework of the online aid decision.
2. The grid incident handling smart navigation method according to claim 1, further comprising:
and establishing a heterogeneous database.
3. The grid incident handling smart navigation method according to claim 2, further comprising:
the method comprises the steps of collecting steady-state data, dynamic data and transient-state data of power grid operation, and storing the steady-state data, the dynamic data and the transient-state data in the heterogeneous database.
4. The grid accident handling intelligent navigation method according to claim 3, wherein the online fault diagnosis of the grid accident and the identification of the online fault event of the grid accident comprise:
retrieving the steady state data, the dynamic data, and the transient data from the heterogeneous database;
and carrying out online fault diagnosis on the power grid accident by using the steady-state data, the dynamic data and the transient data, and identifying an online fault event of the power grid accident.
5. The grid incident handling smart navigation method according to claim 2, further comprising:
and analyzing and refining the incidence relation between the historical fault events of the power grid and the historical external environment information through a data mining technology, and storing the incidence relation in the heterogeneous database.
6. The grid accident handling intelligent navigation method according to claim 5, wherein the obtaining of online external environment information and the generating of the online risk early warning of the online fault event according to the online external environment information include:
acquiring online external environment information through an online monitoring system;
and calling the incidence relation from the heterogeneous database, and generating the risk early warning of the online fault event according to the online external environment information by taking the incidence relation as a basis.
7. The grid incident handling smart navigation method according to claim 2, further comprising:
and establishing an online assistant decision large model based on a dynamic verification method and a soft handover technology, and storing the online assistant decision large model in the heterogeneous database.
8. The grid incident handling smart navigation method according to claim 7, further comprising:
establishing a large model management mechanism for distributed maintenance and real-time sharing of the whole network, and storing the large model management mechanism in the heterogeneous database;
and performing model management on the online assistant decision-making large model in the heterogeneous database by using the large model management mechanism.
9. The grid accident handling intelligent navigation method according to claim 7, wherein the integrating the online risk early warning with the online fault event as an index to form an online aid decision of the online fault event comprises:
calling the online assistant decision large model from the heterogeneous database;
and integrating the online risk early warning into the online decision-making assisting large model by taking the online fault event as an index of the online decision-making assisting large model to form an online decision-making assisting of the online fault event.
10. The utility model provides a grid accident handling intelligent navigation system which characterized in that, grid accident handling intelligent navigation system includes:
a fault event identification module: the system comprises a power grid fault diagnosis module, a power grid fault diagnosis module and a power grid fault diagnosis module, wherein the power grid fault diagnosis module is used for carrying out online fault diagnosis on a power grid fault and identifying an online fault event of the power grid fault;
a risk early warning generation module: the online risk early warning system is used for acquiring online external environment information and generating an online risk early warning of the online fault event according to the online external environment information;
an assistant decision forming module: the online risk early warning is integrated by taking the online fault event as an index to form an online auxiliary decision of the online fault event;
an assistant decision visualization module: a visualization framework for establishing the online assistant decision.
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Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN102117449A (en) * | 2011-03-01 | 2011-07-06 | 国电南瑞科技股份有限公司 | Dynamic verification and soft handover method for online state entering of power grid model |
| CN104868471A (en) * | 2015-06-15 | 2015-08-26 | 国家电网公司 | Static security aid decision making method for provincial power grid |
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| CN104868471A (en) * | 2015-06-15 | 2015-08-26 | 国家电网公司 | Static security aid decision making method for provincial power grid |
| CN107784417A (en) * | 2016-08-31 | 2018-03-09 | 中国电力科学研究院 | The method and system that grid event triggering based on dispatching automation platform calculates |
| CN107133255A (en) * | 2017-03-15 | 2017-09-05 | 中国电力科学研究院 | A kind of bulk power grid full view safety defence method and system |
| CN109978296A (en) * | 2017-12-28 | 2019-07-05 | 南京易司拓电力科技股份有限公司 | A kind of power distribution network aid decision-making system |
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