Developing a Hierarchical Digital Twin Framework for DC Microgrid Implementation

This research introduces a hierarchical digital twin framework for DC microgrids implementation, particularly those utilized in naval power systems. Unlike traditional digital twins, this hierarchical digital twin structure offers a layered perspective. Hierarchical digital twin design promotes computational efficiency by distributing computational burden across a layered configuration that integrates lower-level digital twin blocks with a system digital twin. The layered approach breaks down complex systems into smaller manageable units that can be examined individually and collectively. Central to this strategy is the adoption of a multi-domain and multi-functional technique through the integration of the digital image framework. This allows the digital twin to mirror the physical asset it represents closely, capturing its diverse and complex behaviors in a virtual counterpart. The framework is specifically designed to evaluate the assigned representation task and select the most appropriate digital image for execution, thus ensuring a precise and functional digital representation. Moreover, the hierarchical digital twin is capable of forecasting the behavior of its components, adding a predictive dimension to its functionalities. With its multi-domain, multi-functional approach, coupled with real-time monitoring, predictive analysis, and experimental validation, the hierarchical digital twin framework has the potential to revolutionize the way DC microgrids are managed, especially in naval applications. It represents a shift from reactive to proactive system management, ensuring enhanced performance, improved safety, and extended system lifespan.

Publication Details

Journal
Scholar Commons (University of South Carolina)
Published
2024-08-19
Primary Topic
Magnetic confinement fusion research
Type
article
Field-Weighted Citation Impact
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article

Developing a Hierarchical Digital Twin Framework for DC Microgrid Implementation

Scholar Commons (University of South Carolina)
Magnetic confinement fusion research
article

Developing a Hierarchical Digital Twin Framework for DC Microgrid Implementation

article en

Abstract

This research introduces a hierarchical digital twin framework for DC microgrids implementation, particularly those utilized in naval power systems. Unlike traditional digital twins, this hierarchical digital twin structure offers a layered perspective. Hierarchical digital twin design promotes computational efficiency by distributing computational burden across a layered configuration that integrates lower-level digital twin blocks with a system digital twin. The layered approach breaks down complex systems into smaller manageable units that can be examined individually and collectively. Central to this strategy is the adoption of a multi-domain and multi-functional technique through the integration of the digital image framework. This allows the digital twin to mirror the physical asset it represents closely, capturing its diverse and complex behaviors in a virtual counterpart. The framework is specifically designed to evaluate the assigned representation task and select the most appropriate digital image for execution, thus ensuring a precise and functional digital representation. Moreover, the hierarchical digital twin is capable of forecasting the behavior of its components, adding a predictive dimension to its functionalities. With its multi-domain, multi-functional approach, coupled with real-time monitoring, predictive analysis, and experimental validation, the hierarchical digital twin framework has the potential to revolutionize the way DC microgrids are managed, especially in naval applications. It represents a shift from reactive to proactive system management, ensuring enhanced performance, improved safety, and extended system lifespan.

Scholar Commons (University of South Carolina)
Openalex Percentile: Top 78%
Magnetic confinement fusion research
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Developing a Hierarchical Digital Twin Framework for DC Microgrid Implementation · Scholar Commons (University of South Carolina) (2024) | TGRS Research Map | TGRS