A Real-time Physics Based Digital Twin for Online MOSFET Condition Monitoring in PV Converter Applications

Cappellen, Leander Van; Deckers, Martijn; Alavi, Omid; Daenen, Michaël; Driesen, Johan

doi:10.1109/therminic57263.2022.9950636

Cited by 9 publications

(3 citation statements)

References 10 publications

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“…In electric power conversion, the photovoltaic (PV) dc–dc converter’s efficiency is augmented by thermal cameras and scanning electron microscope imagery. FEM simulations predict temperatures at critical converter components, enabling fast estimations of device conditions under various operational stresses [ 42 ]. The two studies highlight the importance of digital twin predictive maintenance in infrastructure reliability.…”

Section: Resultsmentioning

confidence: 99%

“…Live semantic annotation (LSA) of events and coordination laws that cause the events to evolve Autonomous proactive agents on a coordination platform CLEMAP Develop a series of digital twins that interact and coordinate activities to exchange energy and enhance grid stability [45] In electric power conversion, the photovoltaic (PV) dc-dc converter's efficiency is augmented by thermal cameras and scanning electron microscope imagery. FEM simulations predict temperatures at critical converter components, enabling fast estimations of device conditions under various operational stresses [42]. The two studies highlight the importance of digital twin predictive maintenance in infrastructure reliability.…”

Section: Event Loggermentioning

confidence: 99%

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Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis

Li,

Zhou,

et al. 2024

Sensors

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Digital twin technology has become increasingly popular and has revolutionized data integration and system modeling across various industries, such as manufacturing, energy, and healthcare. This study aims to explore the evolving research landscape of digital twins using Keyword Co-occurrence Network (KCN) analysis. We analyze metadata from 9639 peer-reviewed articles published between 2000 and 2023. The results unfold in two parts. The first part examines trends and keyword interconnection over time, and the second part maps sensing technology keywords to six application areas. This study reveals that research on digital twins is rapidly diversifying, with focused themes such as predictive and decision-making functions. Additionally, there is an emphasis on real-time data and point cloud technologies. The advent of federated learning and edge computing also highlights a shift toward distributed computation, prioritizing data privacy. This study confirms that digital twins have evolved into complex systems that can conduct predictive operations through advanced sensing technologies. The discussion also identifies challenges in sensor selection and empirical knowledge integration.

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Section: Resultsmentioning

confidence: 99%

Section: Event Loggermentioning

confidence: 99%

Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis

Li,

Zhou,

et al. 2024

Sensors

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“…The benefits of interoperable geographical urban DTs are emphasized [21], as well as the effectiveness of DT technology in enhancing understanding of vertical PV system performance [22]. Additionally, real-time temperature estimates provided by DTs contribute to the optimization of PV system performance [23] and, in addition, the capability to restore PV power-voltage characteristics under various conditions [24]. DTs can also optimize D-PV power generation clusters [18] and incorporate hybrid neural networks to enhance PV panel performance in real-world applications [24].…”

Section: Introductionmentioning

confidence: 99%

A Digital Twin Framework for Simulating Distributed Energy Resources in Distribution Grids

Værbak,

Billanes,

Jørgensen

et al. 2024

Energies

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As the adoption of distributed energy resources (DERs) grows, the future of electricity distribution systems is confronted with significant challenges. These challenges arise from the transformation of consumers into prosumers and the resulting increased system complexity, leading to more pressure on the distribution grids. To address this complexity, a Digital Twin framework is designed to simulate DERs within distribution grids effectively. This framework is structured around four key modules: DERs, the electricity distribution grid, the energy management system, and the consumers. It incorporates a communication interface to facilitate interactions among these modules and includes considerations for grid topologies and demand-side configurations. The framework allows for the exploration of various DER adoption rates and capacities. The validation of this framework involves case studies on two Danish distribution grids with scenarios incorporating rooftop photovoltaic (PV) systems, batteries, and electric vehicles, considering different combinations of these technologies. The findings demonstrate the framework’s ability to depict the states of the grid, PV systems, electric vehicles, and battery systems with a 10 min resolution over periods ranging from a day to over a decade.

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From BIM to digital twin in BIPV: A review of current knowledge

Wang,

Xu,

Song

et al. 2024

Sustainable Energy Technologies and Assessments

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A Real-time Physics Based Digital Twin for Online MOSFET Condition Monitoring in PV Converter Applications

Cited by 9 publications

References 10 publications

Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis

Navigating the Evolution of Digital Twins Research through Keyword Co-Occurence Network Analysis

A Digital Twin Framework for Simulating Distributed Energy Resources in Distribution Grids

From BIM to digital twin in BIPV: A review of current knowledge

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