CN109145362A - A kind of power network modeling method and system - Google Patents
A kind of power network modeling method and system Download PDFInfo
- Publication number
- CN109145362A CN109145362A CN201810705142.6A CN201810705142A CN109145362A CN 109145362 A CN109145362 A CN 109145362A CN 201810705142 A CN201810705142 A CN 201810705142A CN 109145362 A CN109145362 A CN 109145362A
- Authority
- CN
- China
- Prior art keywords
- simulation
- model
- information
- database template
- power grid
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 238000000034 method Methods 0.000 title claims abstract description 36
- 238000004088 simulation Methods 0.000 claims abstract description 126
- 230000010354 integration Effects 0.000 claims abstract description 12
- 238000012795 verification Methods 0.000 claims description 15
- 230000006978 adaptation Effects 0.000 claims description 10
- 238000004458 analytical method Methods 0.000 claims description 7
- 238000012544 monitoring process Methods 0.000 claims description 7
- 238000010276 construction Methods 0.000 claims description 4
- 238000001514 detection method Methods 0.000 claims description 3
- 230000001052 transient effect Effects 0.000 claims description 3
- 238000004804 winding Methods 0.000 claims description 3
- 238000005516 engineering process Methods 0.000 abstract description 5
- 238000010586 diagram Methods 0.000 description 9
- 238000012549 training Methods 0.000 description 8
- 238000004590 computer program Methods 0.000 description 7
- 230000008569 process Effects 0.000 description 7
- 238000012545 processing Methods 0.000 description 6
- 238000005520 cutting process Methods 0.000 description 4
- 230000007547 defect Effects 0.000 description 4
- 230000006870 function Effects 0.000 description 4
- 238000003860 storage Methods 0.000 description 4
- 238000004519 manufacturing process Methods 0.000 description 3
- 238000004422 calculation algorithm Methods 0.000 description 2
- 238000004364 calculation method Methods 0.000 description 2
- 210000001503 joint Anatomy 0.000 description 2
- 238000012423 maintenance Methods 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000008602 contraction Effects 0.000 description 1
- 238000003012 network analysis Methods 0.000 description 1
- 230000003287 optical effect Effects 0.000 description 1
- 238000013433 optimization analysis Methods 0.000 description 1
- 238000011176 pooling Methods 0.000 description 1
- 238000003672 processing method Methods 0.000 description 1
- 238000011160 research Methods 0.000 description 1
- 230000009466 transformation Effects 0.000 description 1
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/20—Design optimisation, verification or simulation
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/06—Energy or water supply
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Business, Economics & Management (AREA)
- Physics & Mathematics (AREA)
- Economics (AREA)
- Health & Medical Sciences (AREA)
- General Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- Human Resources & Organizations (AREA)
- Evolutionary Computation (AREA)
- Computer Hardware Design (AREA)
- Public Health (AREA)
- Water Supply & Treatment (AREA)
- General Health & Medical Sciences (AREA)
- Geometry (AREA)
- Marketing (AREA)
- Primary Health Care (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- General Business, Economics & Management (AREA)
- Supply And Distribution Of Alternating Current (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The present invention provides a kind of power network modeling method and system, including the simulating scenes information matches database template based on user；According to database template, the lab environment of server end is established；Simulation model is spliced by the way of graphic and model integration；It will be loaded into the lab environment of server end through spliced simulation model, start simulated environment to generate electric network model.Scheme provided by the invention uses virtual resource resilient expansion technology, solves the disadvantage that traditional emulated physics resource can not be adapted to each other with scale of an exercise, and the height for realizing resource utilizes and the controller perturbation of operation flow.
Description
Technical Field
The invention relates to the technical field of power system simulation, in particular to a power grid modeling method and system.
Background
At present, a regulation and control integrated automation system is generally applied, all levels of power grid companies also pay more and more attention to simulation training of production management personnel, although a traditional dispatcher training simulation system plays an important role in internal training exercises and joint anti-accident exercises, the traditional dispatcher training simulation system still cannot meet the training service requirements of relevant production operation personnel such as dispatchers, monitors, operation and maintenance station operators and the like in a regulation and control integrated new mode and cannot meet the challenge of mass data simulation of a large power grid, and when a complex power grid has a large fault or a natural disaster, the operation personnel often cannot meet the requirement of a large amount of information.
The cloud computing realizes large-scale resource pooling of computing and storage and realizes large-scale economic benefits; the distributed architecture and the load balancing capability realize flexible expansion and contraction of resources according to business requirements; the existing multi-level regulation and control simulation system has insufficient information integration degree and insufficient capability of each unit for cooperatively processing accidents, and a multi-level regulation and control combined training simulation system which is in full range, full process and full scene and is highly consistent with a power grid needs to be built in a targeted manner. The regulation and control integrated system comprises a plurality of levels of scheduling, monitoring, operation and maintenance and power transformation, different personnel need to analyze services by using a power grid model, the object models of different services have large difference, the condition that a plurality of simulation scenes run simultaneously exists, and simultaneously, a plurality of users exist in each scene. How to solve the defect that the traditional simulation physical resources and exercise scale cannot adapt to each other, realizing the on-demand use of a power grid model and the real-time synchronization of the whole network, and realizing the service flow training in accordance with a novel regulation and control integrated operation mode is a research difficulty.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention provides a power grid modeling method and a power grid modeling system based on-demand adaptation, which adopt a virtual resource elastic expansion technology, solve the problem that the traditional simulation physical resource and exercise scale cannot adapt to each other, realize on-demand configuration of a power grid model, and complete on-demand elastic creation of a simulation environment.
In order to achieve the purpose of the invention, the invention adopts the following technical scheme:
a method of modeling a power grid, the method comprising:
matching a database template based on the simulation scene information of the user;
establishing a library environment of a server side according to a database template;
splicing the simulation models in a graph-model integration mode;
and loading the spliced simulation model into a library environment of a server side, and starting the simulation environment to generate a power grid model.
Preferably, before establishing the library environment of the server side according to the database template, the method further includes:
inputting simulation scene information according to a predefined simulation model input range;
matching a database template according to the simulation scene; wherein,
and the input range of the simulation model comprises a region and station list, the level of an external network equivalent buffer area and simulation model parameters.
Further, the definition of the outer net equivalent buffer hierarchy includes: according to the precision of the simulation, an input level is set, wherein the input level is at least 3 layers.
Further, the simulation model parameters comprise a power grid type attribute and a monitoring type attribute;
the power grid type attribute comprises steady-state, dynamic and transient information;
the monitoring type attribute setting includes a standard template, a detailed template, and information whether to include a safety automation device.
Preferably, the simulation scenario information matching database template based on the user comprises:
according to the simulation scene information, a preset matching rule base is utilized to match the database templates one by one;
modifying the matched database template information based on the user information;
and loading the mandatory fields and the optional fields from the matching rule base based on the simulation model parameters.
Further, the database template information comprises record information and domain information of the universal basic model table; the universal basic model table comprises a region table, a station table, a voltage grade table, an interval table, a bus table, a breaker table, a disconnecting link table, a grounding disconnecting link table, a generator table, a line end point table, a transformer table, a winding table, a load table, a capacitive reactance device table and a protection signal table;
the record information includes whether the general basic model table is created and the maximum record number.
Preferably, the establishing a library environment of the server side includes:
creating a scheduling task based on the matched database template information;
completing the establishment of a library environment of a server side based on the scheduling task;
and releasing the database template after the library environment is established.
Further, the establishing a library environment of the server side further includes:
when a plurality of users simultaneously create the library environment of the server side, the matched database template information is modified after the library environment creation of the previous user is finished.
Preferably, the splicing the simulation model in a graph-model integration manner includes:
the cloud platform searches simulation scene information in a predefined simulation model input range, and analyzes the simulation model from the simulation scene information;
when the cloud platform determines that the database template associated with the simulation model does not exist currently, the simulation model is spliced directly, or when the cloud platform determines that the database template associated with the simulation model exists currently, the database template is adopted to splice the current database template
The existing associated database templates are updated.
Preferably, the loading the simulation model into the library environment comprises:
loading a simulation model file containing external network equivalent information into a real-time library environment, and creating a power grid model meeting the input range of the simulation model;
creating graphic information matched with the model and loading the graphic information into a real-time library environment;
and loading section data required by simulation into a real-time library environment, generating a power grid model and verifying the power grid model.
Further, the power grid model verification comprises model rough detection verification, topology analysis verification, protection signal naming rule verification and initial power flow verification.
A power grid modeling system, the system comprising:
the matching module is used for acquiring information of a user and simulation scenes and matching a database template based on the simulation scene information of the user;
the construction module is used for establishing a library environment of the server side according to the database template;
the adaptation module is used for splicing the simulation models in a graph-model integration mode;
and the generation module is used for loading the spliced simulation model into a library environment of the server side and starting the simulation environment to generate the power grid model.
Compared with the closest prior art, the technical scheme provided by the invention has the following beneficial effects:
the invention provides a power grid modeling method and system based on-demand adaptation.A flexible resource technology adapted according to the demand is adopted in the power grid modeling process, and a database template is matched based on the simulation scene information of a user; establishing a library environment of a server side according to a database template; splicing the simulation models in a graph-model integration mode; and loading the spliced simulation model into a library environment of a server side, and starting the simulation environment to generate a power grid model. The scheme can overcome the defect that the traditional simulation physical resources and exercise scale cannot adapt to each other, and realizes the high utilization of resources and the flexible control of business processes.
The dimensionality of a real-time database required by modeling calculation of the power system is often determined to be invariable, the cloud computing technology is fully utilized to flexibly configure the dimensionality of the database, services related to the model are packaged, the power grid model is configured as required, and the on-demand elastic creation of a simulation environment is completed.
Through the subscription of the unified power grid model service of high in clouds, multiple business needs such as regulation and control, fortune dimension, transformer are satisfied, realize nimble the building and the elastic management of power grid model, can improve the resource utilization who simulates the training, promote electric power system personnel's efficiency, make things convenient for electric power system personnel to carry out the electric wire netting analysis fast.
Drawings
Fig. 1 is a general flow chart of power grid modeling based on-demand adaptation in the embodiment of the invention.
Fig. 2 is a schematic diagram of a power grid modeling method based on-demand adaptation in the embodiment of the invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings. The invention provides a power grid modeling method and system based on-demand adaptation, which adopt an on-demand adaptation elastic resource technology in the power grid modeling process, can solve the defect that the traditional simulation physical resource and exercise scale cannot adapt to each other, and realize the high utilization of resources and the elastic control of a business process.
As shown in fig. 1, a method of modeling a power grid, the method comprising:
s1 matching the database template based on the simulation scene information of the user;
s2, establishing a library environment of the server side according to the database template;
s3, splicing the simulation models in a graph-model integration mode;
s4, the spliced simulation model is loaded into a library environment of the server side, and the simulation environment is started to generate a power grid model.
The power grid model is used as the basis of analysis of all power systems and is used for providing support for advanced application software such as similar network analysis, state estimation, load flow calculation, safety analysis and the like, and finally, optimization analysis and auxiliary decision making of the power systems are achieved.
Step S1 includes matching the database template based on the simulation scenario information under the user:
a, matching database templates one by utilizing a preset matching rule base according to simulation scene information; the simulation scenario information referred to herein is the input, the matching rule base is the intermediate processing method, the database template is the output, and the library environment is generated using the database template. For example: the recorded simulation scene information is the requirements of customers, for example, how large a bathroom is without a window, how large a living room is without a balcony, and several bedrooms are needed, the database template is a building drawing (one-room, two-room, four-room, loft and villa), and the actual house is built according to the building drawing in the warehouse environment.
b, modifying the matched database template information based on the user information;
and c, loading the necessary fields and the optional fields from the matching rule base based on the simulation model parameters.
The database template information comprises the record information and the domain information of the universal basic model table; the universal basic model table comprises a region table, a station table, a voltage grade table, an interval table, a bus table, a breaker table, a disconnecting link table, a grounding disconnecting link table, a generator table, a line end point table, a transformer table, a winding table, a load table, a capacitive reactance device table and a protection signal table;
the record information includes whether the general basic model table is created and the maximum number of records.
Step a, matching different types of database templates one by one through a preset matching rule base, including:
the self-learning-based matching algorithm is characterized in that the number of lines and buses of a model is calculated to be X at an initial value, then thresholds of a fuzzy algorithm are set to be 0.2,0.4,0.6 and 0.8, if the actual number of the lines and buses is 0-0.2, 0.2-0.4,0.4-0.6,0.6-0.8 and 0.8-1 of the maximum number of the lines and buses in the whole network, small, medium, large and super-large templates are selected respectively, and a single threshold can be subjected to self-adaptive fuzzy adjustment according to the change selected by an actual user to finally form a final threshold.
Step S2, according to the database template, before establishing the library environment of the server side, further includes:
inputting simulation scene information according to a predefined simulation model input range;
matching a database template according to the simulation scene; wherein, the model input range is obtained by an input tool of a server end,
and the simulation model input range comprises a region and station list, the level of an external network equivalent buffer area and simulation model parameters.
The definition of the outer net equivalent buffer zone level comprises the following steps: according to the precision of the simulation, an input level is set, wherein the input level is at least 3 layers.
The simulation model parameters comprise a power grid type attribute and a monitoring type attribute;
the power grid type attribute comprises steady-state, dynamic and transient information;
the monitoring type attribute settings include standard templates, detailed templates, information whether to include a security automation device.
And step S2, customizing the database template, namely, performing elastic matching on the database template by using the intelligent matching rule base through the module at the server side according to the information input by the scene, so as to realize the maximum utilization of resources. And modifying the database template by matching templates with different dimensions according to the model range entry data obtained in the step S1 by using a predefined matching rule base and modifying corresponding database template information.
Step S2, establishing a library environment of the server side includes:
creating a scheduling task based on the matched database template information;
completing the establishment of a library environment of a server side based on the scheduling task;
and releasing the database template after the library environment is established.
In addition, establishing a library environment at the server side further comprises:
when a plurality of users simultaneously create the library environment of the server side, the matched database template information is modified after the library environment creation of the previous user is finished.
Step S3, splicing the simulation models in a graph-model integration mode comprises the following steps:
the cloud platform searches simulation scene information in a predefined simulation model input range, and analyzes the simulation model from the simulation scene information;
when the cloud platform determines that the database template associated with the simulation model does not exist currently, the simulation model is spliced directly, or when the database template associated with the simulation model is determined to exist currently, the database template is adopted to update the currently existing associated database template.
The specific splicing method mainly comprises three parts of boundary definition, model cutting and model butt joint; wherein the boundary defines: the boundary is a set of devices defining a range between different zones, and in a power system multi-zone model splicing process, a transformer and a line are generally selected as boundary devices.
Cutting a model: the most important link before model splicing is model cutting, model equipment which does not belong to the region is removed from the cutting, redundant description does not exist in the spliced full model, and the distributed modeling thought of who manages who is responsible is reflected.
Model butt joint: after the models of the two sides of the splicing are cut and the taking party of the boundary equipment is determined, the equipment object in the splicing program buffer area is already the spliced full model, and the equipment object is complete and has no loss or redundancy.
Specific embodiments are, for example: province regulations include 6 stations: 123456; the ground tone includes 5 stations: 56789; where 56 is the repeated portion (similar to the boundary), and after model splicing, the full model is 123456789 for a total of 9 stations. Assuming 4 is a level 1 buffer network in the local tone, 3 is a level 2 buffer network in the local tone, 2 is a level 3 buffer network in the local tone, if the local tone only performs a level 1 buffer network, only the 6 stations 456789 are needed, and so on.
Step S4 loading the simulation model into the library environment includes:
loading a simulation model file containing external network equivalent information into a real-time library environment, and creating a power grid model meeting the input range of the simulation model;
creating graphic information matched with the model and loading the graphic information into a real-time library environment;
and loading section data required by simulation into a real-time library environment, generating a power grid model and verifying the power grid model.
The power grid model verification comprises model rough detection verification, topology analysis verification, protection signal naming rule verification and initial power flow verification.
Based on the same technical concept, the invention also provides a power grid modeling system, which comprises:
the matching module is used for acquiring information of a user and simulation scenes and matching a database template based on the simulation scene information of the user;
the construction module is used for establishing a library environment of the server side according to the database template;
the adaptation module is used for splicing the simulation models in a graph-model integration mode;
and the method is used for loading the spliced simulation model into a library environment of the server side, and starting the simulation environment to generate the power grid model.
Wherein, the matching module includes:
the matching unit is used for matching the database templates one by utilizing a preset matching rule base according to the simulation scene information;
the modifying unit is used for modifying the matched database template information based on the user information;
and the field loading unit is used for loading the necessary fields and the optional fields from the matching rule base based on the simulation model parameters.
The construction module comprises:
the scheduling unit is used for establishing a scheduling task based on the matched database template information;
the establishing unit is used for completing the establishment of a library environment of the server side based on the scheduling task;
and the release unit is used for releasing the database template after the library environment is created.
And the waiting unit is used for modifying the matched database template information after the library environment of the previous user is created when a plurality of users create the library environment of the server side at the same time.
An adaptation module comprising:
the analysis unit is used for searching simulation scene information in a predefined simulation model input range by the cloud platform and analyzing the simulation model from the simulation scene information;
and the processing unit is used for directly splicing the simulation models when the cloud platform determines that the database templates associated with the simulation models do not exist currently, or updating the existing associated database templates by adopting the database templates when the cloud platform determines that the database templates associated with the simulation models exist currently.
The generation module comprises:
the file loading unit is used for loading the simulation model file containing the external network equivalent information into a real-time library environment and creating a power grid model meeting the input range of the simulation model;
the creating unit is used for creating the graphic information matched with the model and loading the graphic information into a real-time library environment;
and the generating unit is used for loading the section data required by the simulation into a real-time library environment, generating a power grid model and verifying the power grid model.
As will be appreciated by one skilled in the art, embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Claims (12)
1. A method for modeling a power grid, the method comprising:
matching a database template based on the simulation scene information of the user;
establishing a library environment of a server side according to a database template;
splicing the simulation models in a graph-model integration mode;
and loading the spliced simulation model into a library environment of a server side, and starting the simulation environment to generate a power grid model.
2. The method of claim 1, wherein establishing the server-side library environment according to the database template further comprises:
inputting simulation scene information according to a predefined simulation model input range;
matching a database template according to the simulation scene; wherein,
and the input range of the simulation model comprises a region and station list, the level of an external network equivalent buffer area and simulation model parameters.
3. The method of claim 2, wherein the defining of the outer net equivalent buffer level comprises: according to the precision of the simulation, an input level is set, wherein the input level is at least 3 layers.
4. The method of claim 2, wherein the simulation model parameters include a grid type attribute and a monitoring type attribute;
the power grid type attribute comprises steady-state, dynamic and transient information;
the monitoring type attribute setting includes a standard template, a detailed template, and information whether to include a safety automation device.
5. The method of claim 1, wherein matching the database template based on the simulated scene information under the user comprises:
according to the simulation scene information, a preset matching rule base is utilized to match the database templates one by one;
modifying the matched database template information based on the user information;
and loading the mandatory fields and the optional fields from the matching rule base based on the simulation model parameters.
6. The method of claim 5, wherein the database template information includes record information and domain information of a common base model table; the universal basic model table comprises a region table, a station table, a voltage grade table, an interval table, a bus table, a breaker table, a disconnecting link table, a grounding disconnecting link table, a generator table, a line end point table, a transformer table, a winding table, a load table, a capacitive reactance device table and a protection signal table;
the record information includes whether the general basic model table is created and the maximum record number.
7. The method of claim 1, wherein establishing a server-side library environment comprises:
creating a scheduling task based on the matched database template information;
completing the establishment of a library environment of a server side based on the scheduling task;
and releasing the database template after the library environment is established.
8. The method of claim 7, wherein the establishing a server-side library environment further comprises:
when a plurality of users simultaneously create the library environment of the server side, the matched database template information is modified after the library environment creation of the previous user is finished.
9. The method of claim 1, wherein the splicing the simulation models in a graph-model integration manner comprises:
the cloud platform searches simulation scene information in a predefined simulation model input range, and analyzes the simulation model from the simulation scene information;
when the cloud platform determines that the database template associated with the simulation model does not exist currently, the simulation model is spliced directly, or when the database template associated with the simulation model is determined to exist currently, the database template is adopted to update the currently existing associated database template.
10. The method of claim 1, wherein loading the simulation model into the library environment comprises:
loading a simulation model file containing external network equivalent information into a real-time library environment, and creating a power grid model meeting the input range of the simulation model;
creating graphic information matched with the model and loading the graphic information into a real-time library environment;
and loading section data required by simulation into a real-time library environment, generating a power grid model and verifying the power grid model.
11. The method according to claim 9, wherein the power grid model verification comprises model rough detection verification, topology analysis verification, protection signal naming rule verification and initial power flow verification.
12. A power grid modeling system, the system comprising:
the matching module is used for acquiring information of a user and simulation scenes and matching a database template based on the simulation scene information of the user;
the construction module is used for establishing a library environment of the server side according to the database template;
the adaptation module is used for splicing the simulation models in a graph-model integration mode;
and the generation module is used for loading the spliced simulation model into a library environment of the server side and starting the simulation environment to generate the power grid model.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810705142.6A CN109145362B (en) | 2018-07-02 | Power grid modeling method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201810705142.6A CN109145362B (en) | 2018-07-02 | Power grid modeling method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN109145362A true CN109145362A (en) | 2019-01-04 |
| CN109145362B CN109145362B (en) | 2024-11-12 |
Family
ID=
Cited By (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110175390A (en) * | 2019-05-22 | 2019-08-27 | 南瑞集团有限公司 | A kind of RTDS artificial resource distribution method and its system based on the analysis of more knapsack problems |
| CN111125585A (en) * | 2019-12-24 | 2020-05-08 | 武汉珞珈灵智科技有限公司 | Visualization method and system for Web-end three-dimensional model |
| CN111311082A (en) * | 2020-02-05 | 2020-06-19 | 绍兴大明电力设计院有限公司 | Power distribution design model generation method, device, equipment and storage medium |
| CN112132802A (en) * | 2020-05-27 | 2020-12-25 | 电子科技大学 | Spacecraft collision damage detection method based on self-learning splicing algorithm |
| CN112233512A (en) * | 2020-11-09 | 2021-01-15 | 国网福建省电力有限公司 | Automatic-oriented power distribution automation simulation training method and system |
| CN112464442A (en) * | 2020-11-06 | 2021-03-09 | 广东电网有限责任公司东莞供电局 | Power grid model splicing method and system |
| CN113284257A (en) * | 2021-05-25 | 2021-08-20 | 成都威爱新经济技术研究院有限公司 | Modularized generation and display method and system for virtual scene content |
| CN113359511A (en) * | 2021-06-23 | 2021-09-07 | 陕西工大锐迪信息技术有限公司 | Construction method and device of industrial control simulation network, computer equipment and storage medium |
| CN114092280A (en) * | 2021-11-29 | 2022-02-25 | 国网重庆市电力公司电力科学研究院 | Power grid off-line simulation data fusion splicing method |
| CN114286356A (en) * | 2021-12-29 | 2022-04-05 | 河北电信设计咨询有限公司 | System and method for constructing 5G business model based on database |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040230404A1 (en) * | 2002-08-19 | 2004-11-18 | Messmer Richard Paul | System and method for optimizing simulation of a discrete event process using business system data |
| CN104933638A (en) * | 2015-06-29 | 2015-09-23 | 中国电力科学研究院 | Province-prefecture-county multistage regulate and control joint simulation method |
| CN107193627A (en) * | 2017-03-30 | 2017-09-22 | 中国电力科学研究院 | A kind of simulating scenes creation method and device based on virtualization technology |
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20040230404A1 (en) * | 2002-08-19 | 2004-11-18 | Messmer Richard Paul | System and method for optimizing simulation of a discrete event process using business system data |
| CN104933638A (en) * | 2015-06-29 | 2015-09-23 | 中国电力科学研究院 | Province-prefecture-county multistage regulate and control joint simulation method |
| CN107193627A (en) * | 2017-03-30 | 2017-09-22 | 中国电力科学研究院 | A kind of simulating scenes creation method and device based on virtualization technology |
Non-Patent Citations (2)
| Title |
|---|
| 林静怀;: "基于云计算的电网调度控制培训仿真系统设计", 电力系统自动化 * |
| 米为民 等: "互联电力系统分层分解时空协调建模", 《电力系统自动化》 * |
Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN110175390A (en) * | 2019-05-22 | 2019-08-27 | 南瑞集团有限公司 | A kind of RTDS artificial resource distribution method and its system based on the analysis of more knapsack problems |
| CN110175390B (en) * | 2019-05-22 | 2022-07-08 | 南瑞集团有限公司 | RTDS simulation resource allocation method and system based on multi-knapsack problem analysis |
| CN111125585A (en) * | 2019-12-24 | 2020-05-08 | 武汉珞珈灵智科技有限公司 | Visualization method and system for Web-end three-dimensional model |
| CN111311082A (en) * | 2020-02-05 | 2020-06-19 | 绍兴大明电力设计院有限公司 | Power distribution design model generation method, device, equipment and storage medium |
| CN112132802B (en) * | 2020-05-27 | 2022-06-14 | 电子科技大学 | Spacecraft collision damage detection method based on self-learning splicing algorithm |
| CN112132802A (en) * | 2020-05-27 | 2020-12-25 | 电子科技大学 | Spacecraft collision damage detection method based on self-learning splicing algorithm |
| CN112464442A (en) * | 2020-11-06 | 2021-03-09 | 广东电网有限责任公司东莞供电局 | Power grid model splicing method and system |
| CN112233512A (en) * | 2020-11-09 | 2021-01-15 | 国网福建省电力有限公司 | Automatic-oriented power distribution automation simulation training method and system |
| CN113284257A (en) * | 2021-05-25 | 2021-08-20 | 成都威爱新经济技术研究院有限公司 | Modularized generation and display method and system for virtual scene content |
| CN113359511A (en) * | 2021-06-23 | 2021-09-07 | 陕西工大锐迪信息技术有限公司 | Construction method and device of industrial control simulation network, computer equipment and storage medium |
| CN114092280A (en) * | 2021-11-29 | 2022-02-25 | 国网重庆市电力公司电力科学研究院 | Power grid off-line simulation data fusion splicing method |
| CN114092280B (en) * | 2021-11-29 | 2024-04-09 | 国网重庆市电力公司电力科学研究院 | Power grid offline simulation data fusion splicing method |
| CN114286356A (en) * | 2021-12-29 | 2022-04-05 | 河北电信设计咨询有限公司 | System and method for constructing 5G business model based on database |
| CN114286356B (en) * | 2021-12-29 | 2024-07-30 | 河北电信设计咨询有限公司 | System and method for constructing 5G service model based on database |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN106960103B (en) | Automatic generation method and device of power grid graph | |
| CN105843182B (en) | A kind of power scheduling accident prediction system and method based on OMS | |
| Xu et al. | A decomposition-based practical approach to transient stability-constrained unit commitment | |
| CN107330056A (en) | Wind power plant SCADA system and its operation method based on big data cloud computing platform | |
| CN104463465B (en) | A kind of real time monitoring clustering methods based on distributed model | |
| CN107516895A (en) | Power distribution network rapid simulation method and device, storage medium and computer equipment thereof | |
| CN104933638A (en) | Province-prefecture-county multistage regulate and control joint simulation method | |
| CN103778230A (en) | Online automatic generation method for black-start scheme | |
| KR101759893B1 (en) | Virtual device management apparatus based on scenario for distributed energy resources | |
| CN112260322A (en) | Source network load storage simulation platform, method and system | |
| CN111082521A (en) | Operation and maintenance data monitoring method and operation and maintenance system of power grid regulation and control system | |
| CN106356850A (en) | Safety and stability control device fault offline control strategy model generation method | |
| CN113361108B (en) | Electric power system future time period simulation method and system based on real-time and predicted data | |
| CN109614706A (en) | A kind of numeral simulation analysis management system | |
| CN111652760B (en) | Power grid operation and maintenance virtual reality simulation system and simulation method | |
| CN104537168B (en) | The comprehensively monitoring simulation training system model data management method of equipment oriented function | |
| CN110361609A (en) | Extra-high voltage equipment monitors system and method | |
| Ortiz-Villalba et al. | Optimizing system operation with nadir considerations via simulations of detailed system dynamic responses | |
| Popović et al. | A novel cloud-based advanced distribution management system solution | |
| CN109145362A (en) | A kind of power network modeling method and system | |
| JP2000112515A (en) | System simulating device and computer readable storage medium | |
| CN109145362B (en) | Power grid modeling method and system | |
| CN108767845B (en) | Flexible simulation method and system | |
| CN116360294A (en) | Simulation method and device based on active power distribution network | |
| CN116522643A (en) | Automatic construction method and system for power grid operation simulation scheme library |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant |