CN115688439A - Reservoir model construction method based on digital twinning - Google Patents
Reservoir model construction method based on digital twinning Download PDFInfo
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- CN115688439A CN115688439A CN202211376537.9A CN202211376537A CN115688439A CN 115688439 A CN115688439 A CN 115688439A CN 202211376537 A CN202211376537 A CN 202211376537A CN 115688439 A CN115688439 A CN 115688439A
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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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Abstract
The invention provides a reservoir model construction method based on digital twins, which specifically comprises the following steps: s1, collecting various data of a reservoir; s2, establishing a physical model, a conditional model and a digital model; s3, setting data interaction interfaces among the physical models, the conditional models and the digital models to enable the physical models, the conditional models and the digital models to carry out data interaction; s4, analyzing and simulating the reservoir according to the historical data and the scheduling decision; s5, optimizing data interaction of each model; s6, repeating the steps S4-S5 to obtain a reservoir digital twin model; and S7, acquiring data and scheduling decisions in real time, and simulating the running state of the reservoir. The invention can comprehensively consider the conditions of reservoir capacity, water level, scheduling, silt deposition and the like, simulate the operation and decision results of the reservoir, obtain a reservoir model which can be visually displayed, is beneficial to monitoring the operation of the reservoir and can provide technical support for decision optimization.
Description
Technical Field
The invention relates to the technical field of water conservancy, in particular to a reservoir model construction method based on digital twins.
Background
The reservoir is the hydro-junction engineering that can block flood, impound and adjust rivers, undertakes important functions such as flood control, irrigation, electricity generation and shipping. The digital twin technology is characterized in that data such as a physical model, sensor updating, operation history and the like are fully utilized, a multidisciplinary, multi-physical quantity, multi-scale and multi-probability simulation process is integrated, digital mapping is completed in a virtual space, and therefore the full life cycle simulation operation process of the physical entity reservoir is truly reflected.
In the operation and scheduling of the reservoir, the correlation among all parameters is complex, the number of related indexes is large, and the parameters and decisions are in a constantly changing state, so that the simulation and prediction are difficult to perform. The invention provides a simulation method for the dynamic process of reservoir operation and scheduling by introducing the technology of digital twinning.
Disclosure of Invention
The invention aims to overcome the defects of the prior art and provides a reservoir model construction method based on digital twins, which is specifically realized by the following technical scheme:
the invention provides a reservoir model construction method based on digital twins, which comprises the following steps:
s1, collecting actual size data, historical hydrological data and historical scheduling decision data of a reservoir;
s2, establishing a three-dimensional entity physical model according to the actual size of the reservoir; establishing a conditioned model for the warehousing traffic and the ex-warehouse traffic; establishing a digital model for reservoir capacity, water level, scheduling, power generation flow and silt deposition power generation power;
s3, setting data interaction interfaces among the physical models, the conditional models and the digital models to enable the physical models, the conditional models and the digital models to carry out data interaction;
s4, analyzing the reservoir according to historical hydrological data and scheduling decisions, setting initial conditions, and performing simulation;
s5, optimizing data interaction among the physical models, the conditional models and the digital models according to the simulation conditions;
s6, repeating the steps S4-S5 to obtain a reservoir digital twin model;
s7, collecting various data and scheduling decision data of the reservoir in real time, and simulating the running state of the reservoir through a reservoir digital twin model.
Optionally or preferably, the three-dimensional solid model established according to the actual size of the reservoir can perform space motion and display the operation state under the mapping of any data in each digital model.
Optionally or preferably, in step S4, performing correlation analysis on the multiple hydrological data and the scheduling decision, and establishing a joint model.
Optionally or preferably, in step S4, the method further includes dividing historical hydrologic data into a dry period, a flat period and a rich period; different initial conditions corresponding to the dry season, the flat season and the rich season are set respectively, and simulation is carried out respectively.
Optionally or preferably, in step S5, the simulation situation includes simulation time consumption, simulation result error, and secondary relevance data operation proportion.
Based on the technical scheme, the following technical effects can be generated:
the reservoir model construction method based on the digital twin can comprehensively consider the conditions of reservoir capacity, water level, power generation flow, scheduling, sediment deposition and the like, simulate the operation and decision results of the reservoir, obtain the reservoir model capable of being visually displayed, contribute to monitoring the operation of the reservoir and provide technical support for decision optimization.
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. The drawings in the following description are only one embodiment of the invention, and other drawings can be obtained from the structures shown in the drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of the process of the present invention.
Detailed Description
It should be understood that the detailed description and specific examples, while indicating the invention, are intended for purposes of illustration only and are not intended to limit the scope of the invention. It is to be understood that the described embodiments are merely some embodiments of the invention, and not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, are within the scope of the present invention.
As shown in fig. 1:
the invention provides a reservoir model construction method based on digital twins, which comprises the following steps:
s1, collecting actual size data, historical hydrological data and historical scheduling decision data of a reservoir;
s2, establishing a three-dimensional entity physical model according to the actual size of the reservoir; establishing a conditioned model for the warehousing traffic and the ex-warehouse traffic; establishing a digital model for reservoir capacity, water level, scheduling, power generation flow and silt deposition power generation power;
s3, data interaction interfaces are arranged among the physical models, the conditional models and the digital models, so that data interaction can be carried out among the physical models, the conditional models and the digital models, and the physical models of the reservoir can carry out space motion and show the running state under the mapping of any data in the digital models;
s4, analyzing the reservoir according to the historical hydrological data and the scheduling decision data, setting initial conditions, and performing simulation;
s5, optimizing data interaction among the physical models, the conditional models and the digital models according to simulation conditions;
s6, repeating the steps S4-S5 to obtain a reservoir digital twin model;
and S7, collecting various data and scheduling decision data of the reservoir in real time, and simulating the running state of the reservoir through a reservoir digital twin model.
In this embodiment, in step S4, correlation analysis is performed on the multiple pieces of hydrological data and scheduling decision data, and the hydrological data and the scheduling decision data may be first established as a joint model and then analyzed, or the hydrological data and the scheduling decision data may be analyzed separately.
In this embodiment, in step S4, when the time difference of the historical hydrographic data is large, the historical hydrographic data may be divided into a dry period, a flat period, and a rich period according to the time interval characteristics; different initial conditions corresponding to the dry season, the normal season and the rich season are set in each time interval respectively, and simulation is carried out respectively. The model can be selected according to actual conditions when the model is actually applied.
In this embodiment, in step S5, the simulation condition includes simulation time consumption, simulation result error, and secondary relevance data operation proportion.
Claims (5)
1. A reservoir model construction method based on digital twinning is characterized in that: the method comprises the following steps:
s1, collecting actual size data, historical hydrological data and historical scheduling decision data of a reservoir;
s2, establishing a three-dimensional entity physical model according to the actual size of the reservoir; establishing a conditioned model for the warehousing traffic and the ex-warehouse traffic; establishing a digital model for reservoir capacity, water level, scheduling, power generation flow and silt deposition power generation power;
s3, setting data interaction interfaces among the physical models, the conditional models and the digital models to enable the physical models, the conditional models and the digital models to carry out data interaction;
s4, analyzing the reservoir according to historical hydrological data and scheduling decisions, setting initial conditions, and performing simulation;
s5, optimizing data interaction among the physical models, the conditional models and the digital models according to simulation conditions;
s6, repeating the steps S4-S5 to obtain a reservoir digital twin model;
s7, collecting various data and scheduling decision data of the reservoir in real time, and simulating the running state of the reservoir through a reservoir digital twin model.
2. The reservoir model building method based on the digital twin as claimed in claim 1, wherein: the three-dimensional solid model established according to the actual size of the reservoir can perform space motion and show the running state under the mapping of any data in each digital model.
3. The reservoir model building method based on the digital twin as claimed in claim 1, wherein: in step S4, correlation analysis is performed on the multiple hydrological data and the scheduling decision data, and a joint model is established.
4. The reservoir model building method based on the digital twin as claimed in claim 1, wherein: in step S4, dividing historical hydrological data into a dry period, a flat period and a rich period; different initial conditions corresponding to the dry season, the flat season and the rich season are set respectively, and simulation is carried out respectively.
5. The reservoir model building method based on the digital twin as claimed in claim 1, wherein: in step S5, the simulation condition includes simulation time consumption, simulation result error, and secondary relevance data operation proportion.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116595898A (en) * | 2023-07-18 | 2023-08-15 | 水利部交通运输部国家能源局南京水利科学研究院 | Method and system for quantitatively analyzing water blocking superposition influence of plain river bridge group |
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN116595898A (en) * | 2023-07-18 | 2023-08-15 | 水利部交通运输部国家能源局南京水利科学研究院 | Method and system for quantitatively analyzing water blocking superposition influence of plain river bridge group |
| CN116595898B (en) * | 2023-07-18 | 2023-09-19 | 水利部交通运输部国家能源局南京水利科学研究院 | Method and system for quantitatively analyzing water blocking superposition influence of plain river bridge group |
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