Insights into Digital Twin Based on Finite Element Simulation of a Large Hydro Generator

Moussa, Cynthia; AI-Haddad, Kamal; Kedjar, Bachir; Merkhouf, Arezki

doi:10.1109/iecon.2018.8591653

Cited by 21 publications

(9 citation statements)

References 4 publications

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“…-I: Cyberphysical analysis of the energy systems with Internet of Things (IoT) and cloud computing [74] -I: Detection and analysis of anomalies in flexible energy deployments [97] -E: Grid control enablement through Digital Dynamic Mirror (DDM) [98] -E: Operations and scheduling of microgrid energy storage using optimization models [99] -G: Cyber resiliency analysis of networked microgrids by leveraging Amazon Web Services (AWS) [100] -I: Maintenance and fault diagnosis of power grid equipment/systems/assets including transmission lines [101] -P: Power converters condition monitoring [102] -I: Windfarm fault/failure predictive maintenance; distributed PV fault diagnosis [103] -M: Prosumer infrastructure ontological modeling to identify optimal configuration of hybrid power system with renewable energy sources [104] -M: Operations analysis, energy economic studies, and optimization modeling for coal-fired thermal power plants [105] -I: Prediction of useful life of offshore wind turbine power converters to facilitate proactive maintenance [106] -M: Finite element method-based digital twin models for hydro power generators [107] -M: Coordination of multivector energy systems combined with machine learning and real-time IoT integration to facilitate optimal control, scheduling, forecasting of energy assets, and pertinent energy management processes/tool [108] -I: Design of intelligent digital twin for cyber-physical production systems using heterogenous data acquisition and data integration [109] -M: Rooftop PV system studies/analysis [76] -M: Evaluation of net zero buildings [110] Table A2. Cont.…”

Section: Refmentioning

confidence: 99%

A Theoretical Open Architecture Framework and Technology Stack for Digital Twins in Energy Sector Applications

et al. 2023

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Digital twin is often viewed as a technology that can assist engineers and researchers make data-driven system and network-level decisions. Across the scientific literature, digital twins have been consistently theorized as a strong solution to facilitate proactive discovery of system failures, system and network efficiency improvement, system and network operation optimization, among others. With their strong affinity to the industrial metaverse concept, digital twins have the potential to offer high-value propositions that are unique to the energy sector stakeholders to realize the true potential of physical and digital convergence and pertinent sustainability goals. Although the technology has been known for a long time in theory, its practical real-world applications have been so far limited, nevertheless with tremendous growth projections. In the energy sector, there have been theoretical and lab-level experimental analysis of digital twins but few of those experiments resulted in real-world deployments. There may be many contributing factors to any friction associated with real-world scalable deployment in the energy sector such as cost, regulatory, and compliance requirements, and measurable and comparable methods to evaluate performance and return on investment. Those factors can be potentially addressed if the digital twin applications are built on the foundations of a scalable and interoperable framework that can drive a digital twin application across the project lifecycle: from ideation to theoretical deep dive to proof of concept to large-scale experiment to real-world deployment at scale. This paper is an attempt to define a digital twin open architecture framework that comprises a digital twin technology stack (D-Arc) coupled with information flow, sequence, and object diagrams. Those artifacts can be used by energy sector engineers and researchers to use any digital twin platform to drive research and engineering. This paper also provides critical details related to cybersecurity aspects, data management processes, and relevant energy sector use cases.

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Section: Refmentioning

confidence: 99%

A Theoretical Open Architecture Framework and Technology Stack for Digital Twins in Energy Sector Applications

et al. 2023

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“…Liu et al [178,179] proposed an intelligent management platform for coal mine electromechanical equipment based on the IoT, effectively reduces the probability of equipment failure, improves the level of equipment refinement management, and realizes the whole life cycle management of equipment. Moussa et al [114] proposed a digital twin model for large hydroelectric generators. To improve the accuracy and efficiency of prediction and health management of wind power, Tao et al [112,[180][181][182][183] proposed a digital twin failure prediction model for complex equipment, which effectively utilized the interaction mechanism of digital twin and data fusion techniques.…”

Section: The Applicationsmentioning

confidence: 99%

Digital Twin for Integration of Design-Manufacturing-Maintenance: An Overview

Zhu

et al. 2022

Chin. J. Mech. Eng.

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Traditional design, manufacturing and maintenance are run and managed independently under their own rules and regulations in an increasingly time-and-cost ineffective manner. A unified platform for efficient and intelligent design-manufacturing-maintenance of mechanical equipment and systems is highly needed in this rapidly digitized world. In this work, the definition of digital twin and its research progress and associated challenges in the design, manufacturing and maintenance of engineering components and equipment were thoroughly reviewed. It is indicated that digital twin concept and associated technology provide a feasible solution for the integration of design-manufacturing-maintenance as it has behaved in the entire lifecycle of products. For this aim, a framework for information-physical combination, in which a more accurate design, a defect-free manufacturing, a more intelligent maintenance, and a more advanced sensing technology, is prospected.

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“…The work developed in [12] derives an electromagnetic FEM model of a large hydro generator to be used as a digital twin. As the FEM model showed its capability to perform reliable simulations in several conditions, e.g., noload, rated load, and overexcited, the digital twin based on this model should aid the diagnosis and maintenance scheme of the generator, which is helpful and convenient for large machines.…”

Section: Physics-based Modellingmentioning

confidence: 99%

Extending the Multiphysics Modelling of Electric Machines in a Digital Twin Concept

Mendes

Ferreira

2021

2021 11th IEEE International Conference on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applicat

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The digital twin is a trending technology that has been applied to different fields. In this work, the use of the digital twin of electric machines in a life cycle perspective is investigated. It presents a literature review of the main concepts and applications of the digital twin in the field. In addition, it discusses the methodological approach to obtain the digital twin of a static electric machine by using its multiphysics model in a reduced order model, to improve the maintenance scheme and estimate the lifetime of its insulation system based on the machine's temperature profile.

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Insights into Digital Twin Based on Finite Element Simulation of a Large Hydro Generator

Cited by 21 publications

References 4 publications

A Theoretical Open Architecture Framework and Technology Stack for Digital Twins in Energy Sector Applications

A Theoretical Open Architecture Framework and Technology Stack for Digital Twins in Energy Sector Applications

Digital Twin for Integration of Design-Manufacturing-Maintenance: An Overview

Extending the Multiphysics Modelling of Electric Machines in a Digital Twin Concept

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