scholarly journals APPLICATION OF EDGE ANALYTICS TECHNOLOGY TO DEVELOP DIGITAL TWINS OF RUSSIA’S UNITED ELECTRIC POWER SYSTEM FACILITIES

2021 ◽  
pp. 28-39
Author(s):  
Ирина Николаевна Колосок ◽  
Елена Сергеевна Коркина
Keyword(s):  
Power System ◽  
Information Source ◽  
Electric Power System ◽  
Information Support ◽  
Digital Twin ◽  
Energy Facility ◽  
Digital Twins ◽  
Digital Substation ◽  
And Control ◽  
And Storage

Технология цифровых двойников является одной из базовых технологий в процессе «цифровизации» энергетики. Важным компонентом цифрового двойника является сбор данных с физического объекта для мониторинга и управления этим объектом. Современные средства информационного обеспечения задач управления режимами ЕЭС России - SCADA и СМПР - предоставляют в центры диспетчерского управления огромные объемы информации, которая может быть использована для создания цифрового двойника отдельного объекта энергетики или всей энергосистемы в целом. В статье для снижения объемов и стоимости передачи и хранения больших объемов данных при создании цифровых двойников объектов энергетики предлагается использовать технологию «Edge Analytics» - граничной аналитики, которая позволяет осуществлять сбор, обработку и анализ данных на периферийных устройствах сети рядом с источником информации. В качестве объекта для создания цифрового двойника рассматривается современная цифровая подстанция. The technology of digital twins is a basic one in the process of energy "digitalization." An essential component of the digital twin development is data collection from a physical facility to monitor and control this facility. Advanced information support systems designed to control the UES of Russia (SCADA and WAMS) provide control centers with considerable amounts of information, which can be used to create a digital twin of an individual energy facility or entire power system. This paper proposes the use of edge analytics technology that enables the collection, processing, and analysis of data on network peripheral units near the information source, to reduce the amount and cost of transmission and storage of a whole host of data when creating digital twins of energy facilities. A modern digital substation is considered as a facility to be digitally twinned.

Harmonic Analysis of Non-Sinusoidal Harmonic Signals in Electric Power System

2014 ◽  
Vol 1070-1072 ◽  
pp. 779-784
Author(s):  
Dan Luo ◽  
Yi Xiao ◽  
Jie Na Zhou
Keyword(s):  
Power System ◽  
Harmonic Analysis ◽  
Short Range ◽  
Time Windows ◽  
Electric Power System ◽  
Normal Operation ◽  
Calculation Error ◽  
Interpolation Algorithm ◽  
Harmonic Signals ◽  
And Control

Harmonic Analysis and control is very important for the power system because harmonics have serious harm to its normal operation. Harmonic Analysis uses fast Fourier transform (FFT) to solve this problem though it causes the spectrum leakage which Increases the calculation error. To solve this problem, the interpolation algorithm combine with tapered time windows are used. The tapered time windows solve the long-range leakage and the interpolation algorithm solves the problem of short-range leakage.

Development and Assessment of a Nearly Autonomous Management and Control System During a Single Loss of Flow Accident

2020 ◽  
Author(s):  
Linyu Lin ◽  
Paridhi Athe ◽  
Pascal Rouxelin ◽  
Nam Dinh ◽  
Jeffrey Lane
Keyword(s):  
Knowledge Base ◽  
Confusion Matrix ◽  
Data Generation ◽  
Digital Twin ◽  
Control Functions ◽  
Digital Twins ◽  
Twin Models ◽  
Autonomous Management ◽  
And Performance ◽  
And Control

Abstract In this work, a Nearly Autonomous Management and Control (NAMAC) system is designed to diagnose the reactor state and provide recommendations to the operator for maintaining the safety and performance of the reactor. A three layer-hierarchical workflow is suggested to guide the design and development of the NAMAC system. The three layers in this workflow corresponds to knowledge base, digital twin developmental layer (for different NAMAC functions), and NAMAC operational layer. Digital twin in NAMAC is described as knowledge acquisition system to support different autonomous control functions. Therefore, based on the knowledge base, a set of digital twin models is trained to determine the plant state, predict behavior of physical components or systems, and rank available control options. The trained digital twin models are assembled according to NAMAC operational workflow to support decision-making process in selecting the optimal control actions during an accident scenario. To demonstrate the capability of the NAMAC system, a case study is designed, where a baseline NAMAC is implemented for operating a simulator of the Experimental Breeder Reactor II (EBR-II) during a single loss of flow accident. Training database for development of digital twin models is obtained by sampling the control parameters in the GOTHIC data generation engine. After the training and testing, the digital twins are assembled into a NAMAC system according to the operational workflow. This NAMAC system is coupled with the GOTHIC plant simulator, and a confusion matrix is generated to illustrate the accuracy and robustness of implemented NAMAC system. It is found that within the training databases, NAMAC can make reasonable recommendations with zero confusion rate. However, when the scenario is beyond the training cases, the confusion rate increases, especially when the scenarios are more severe. Therefore, a discrepancy checker is added to detect unexpected reactor states and alert operators for safety-minded actions.

scholarly journals Digital Twins-Based Smart Design and Control of Ultra-Precision Machining: A Review

Symmetry ◽  
2021 ◽  
Vol 13 (9) ◽  
pp. 1717
Author(s):  
Lei Wu ◽  
Jiewu Leng ◽  
Bingfeng Ju
Keyword(s):  
Information Asymmetry ◽  
Large Scale ◽  
Planning Process ◽  
Design Stage ◽  
Precision Machining ◽  
Digital Twin ◽  
Module Design ◽  
Digital Twins ◽  
Ultra Precision ◽  
And Control

Ultra-Precision Machining (UPM) is a kind of highly accurate processing technology developed to satisfy the manufacturing requirements of high-end cutting-edge products including nuclear energy producers, very large-scale integrated circuits, lasers, and aircraft. The information asymmetry phenomenon widely exists in the design and control of ultra-precision machining. It may lead to inconsistency between the designed performance and operational performance of the UPM equipment on stiffness, thermal stability, and motion accuracy, which result from its design, manufacturing, and control, and determine the form accuracy and surface roughness of machined parts. The performance of the UPM equipment should be improved continuously. It is still challenging to realize the real-time and self-adaptive control, in which building a high-fidelity and computationally efficient digital twin is a valuable solution. Nevertheless, the incorporation of the digital twin technology into the UPM design and control remains vague and sometimes contradictory. Based on a literature search in the Google Scholar database, the critical issues in the UPM design and control, and how to use the digital twin technologies to promote it, are reviewed. Firstly, the digital twins-based UPM design, including bearings module design, spindle-drive module design, stage system module design, servo module design, and clamping module design, are reviewed. Secondly, the digital twins-based UPM control studies, including voxel modeling, process planning, process monitoring, vibration control, and quality prediction, are reviewed. The key enabling technologies and research directions of digital twins-based design and control are discussed to deal with the information asymmetry phenomenon in UPM.

scholarly journals A New Concept of Digital Twin Supporting Optimization and Resilience of Factories of the Future

2020 ◽  
Vol 10 (13) ◽  
pp. 4482 ◽  
Author(s):  
Adrien Bécue ◽  
Eva Maia ◽  
Linda Feeken ◽  
Philipp Borchers ◽  
Isabel Praça
Keyword(s):  
Cognitive Modeling ◽  
Monitoring And Control ◽  
Security Testing ◽  
Digital Twin ◽  
Digital Twins ◽  
Support Tools ◽  
The Future ◽  
And Control ◽  
Comprehensive Modeling ◽  
Factories Of The Future

In the context of Industry 4.0, a growing use is being made of simulation-based decision-support tools commonly named Digital Twins. Digital Twins are replicas of the physical manufacturing assets, providing means for the monitoring and control of individual assets. Although extensive research on Digital Twins and their applications has been carried out, the majority of existing approaches are asset specific. Little consideration is made of human factors and interdependencies between different production assets are commonly ignored. In this paper, we address those limitations and propose innovations for cognitive modeling and co-simulation which may unleash novel uses of Digital Twins in Factories of the Future. We introduce a holistic Digital Twin approach, in which the factory is not represented by a set of separated Digital Twins but by a comprehensive modeling and simulation capacity embracing the full manufacturing process including external network dependencies. Furthermore, we introduce novel approaches for integrating models of human behavior and capacities for security testing with Digital Twins and show how the holistic Digital Twin can enable new services for the optimization and resilience of Factories of the Future. To illustrate this approach, we introduce a specific use-case implemented in field of Aerospace System Manufacturing.

Sign in / Sign up

Export Citation Format

Share Document