Applications and challenges of digital twins of floating wind turbines DOI
Maria-Styliani Daraki, B. L. Mina,

Muhnad Almasoudi

et al.

Published: Jan. 1, 2024

A digital twin is a virtual model of physical asset, like wind turbine, synchronized with real-time data to provide insights into its performance, condition, and behavior. This technology has applications in environmental perception, condition assessment, predictive maintenance, anomaly detection, optimizing the operational parameters floating offshore turbines. paper reviews current state research practical twins this field. It explores concept, focusing on challenges posed by climate, system dynamics, structural issues Case studies include topics such as Fatigue Limit State, pitch blade control, drivetrain power output, strain. Technical implementing related collection, transfer, communication, standardization, well robustness models accurately simulating behaviors. Solutions can be found through AI, IoT, advanced simulation tools, improved monitoring techniques. Non-technical challenges, typical for emerging technologies, are mainly tied human factors. However, benefits financial advantages expected promote widespread adoption industrial applications.

Language: Английский

DIGITILISING THE ENERGY SECTOR: A COMPREHENSIVE DIGITAL TWIN FRAMEWORK FOR BIOMASS GASIFICATION POWER PLANT WITH CO2 CAPTURE DOI Creative Commons
Peter Akhator, Bilainu Oboirien

Cleaner Energy Systems, Journal Year: 2025, Volume and Issue: unknown, P. 100175 - 100175

Published: Jan. 1, 2025

Language: Английский

Citations

0
Innovative Horizons for Sustainable Smart Energy: Exploring the Synergy of 5G and Digital Twin Technologies DOI

Mirjana Maksimović,

Srđan Jokić,

Marko Bošković

et al.

Process Integration and Optimization for Sustainability, Journal Year: 2025, Volume and Issue: unknown

Published: Jan. 14, 2025

Language: Английский

Citations

0
Cyber threat intelligence for smart grids using knowledge graphs, digital twins, and hybrid machine learning in SCADA networks DOI Creative Commons
Nabeel Al-Qirim, Munir Majdalawieh, Anoud Bani-Hani

et al.

International Journal of Engineering Business Management, Journal Year: 2025, Volume and Issue: 17

Published: March 1, 2025

In the SCADA (Supervisory Control and Data Acquisition) network of a smart grid, switch is connected to multiple Intelligent Electronic Devices (IEDs) that are based on protective relays. False-Data Injection Attacks (FDIA), Remote-Tripping Command (RTCI), System Reconfiguration (SRA) three types cyber-attacks networks, resulting in single-line-to-ground (SLG) fault, IED-relay failure, circuit-breaker open issues occur. The existing cyber threat intelligence (CTI) approaches grids unable provide visualization cyber-attacking grid effects. To understand full effect attacks, there need for knowledge-graph method-based digital-twin cyber-attack approach which missing systems. This study presents novel “Digital-twin Machine Learning-based Cyber Threat Intelligence (DT-ML-SCADA-CTI)” approach, utilizes an innovative algorithm visualize predict effects cyber-attacks, including FDIA, RTCI, SRA, process begins with data transformation generate data, then analyzed attack prediction using machine learning models such as Extra-Trees, XGBoost, Random Forest, Bootstrap Aggregating, Logistic Regression. further enhance analysis, directed-graph (DiGraph) applied create knowledge-graph-based digital twin, allowing deeper understanding how these impact operations. comparison demonstrates superiority proposed it offers more detailed clearer representation enhanced provides insights into dynamics significantly improves predictive accuracy, showcasing effectiveness method mitigating threats.

Language: Английский

Citations

0
Towards zero emission: exploring innovations in wind turbine design for sustainable energy a comprehensive review DOI

G. Omer-Alsultan,

Ahmad Alsahlani,

G. Mohamed-Alsultan

et al.

Service Oriented Computing and Applications, Journal Year: 2024, Volume and Issue: unknown

Published: Nov. 25, 2024

Language: Английский

Citations

3
A Conceptual Framework for Digital Twin in Healthcare: Evidence from a Systematic Meta-Review DOI Creative Commons
Giulia Pellegrino, Massimiliano Gervasi, Mario Angelelli

et al.

Information Systems Frontiers, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 12, 2024

Language: Английский

Citations

2
Digital Twin Technology in Built Environment: A Review of Applications, Capabilities and Challenges DOI Open Access

Yalda Mousavi,

Zahra Gharineiat,

Armin Aghakarimi

et al.

Published: July 12, 2024

Digital Twin (DT) technology is a pivotal innovation within the built environment industry, facilitating digital transformation through advanced data integration and analytics. DTs have demonstrated significant benefits in building design, construction, asset management, including optimizing lifecycle energy use, enhancing operational efficiency, enabling predictive maintenance, improving user adaptability. By integrating real-time from IoT sensors with analytics, provide dynamic actionable insights for better decision-making resource management. Despite these promising benefits, several challenges impede widespread adoption of DT technology, such as technological integration, consistency, organisational adaptation, cybersecurity concerns. Addressing requires inter-disciplinary collaboration, standardization formats, development universal design platforms DTs. This paper provides comprehensive review definitions, applications, capabilities, Architecture, Engineering, Construction (AEC) industries. important researchers professionals, helping them gain more detailed view DT. The findings also demonstrate impact that can on this sector, contributing to advancing implementations promoting sustainable efficient management practices. Ultimately, set revolutionize AEC industries by autonomous, data-driven operations enhanced productivity performance.

Language: Английский

Citations

1
Building a Digital Twin for a Ground Heat Exchanger DOI
Montaser Mahmoud, Concetta Semeraro, Mohamad Ramadan

et al.

Chemical Engineering & Technology, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 6, 2024

Abstract This research investigates the development of a digital twin (DT) for ground heat exchangers (GHEs) and its potential to enhance efficiency sustainability shallow geothermal energy systems. It introduces an innovative approach building GHE‐DT that connects physical systems monitor key parameters, predict issues, optimize efficiency. The process involves several phases including implicit knowledge codification, data‐driven analysis, model construction, system design. study emphasizes real‐time monitoring effective parameters: temperature fluid conditions (flow rate, temperature, pressure). GHE‐DT's mainly comprises three sections, namely, data storage, mathematical modeling, modeling. role presented is simulate GHE's behavior assess performance characteristics, such as exchanger's effectiveness Additionally, used in proposed DT utilizes formal concept analysis relation identify connections associations among parameters better understanding GHE functioning. provides useful services trend problem prediction, correlation analysis. These provide engineers operators with opportunity increase dependability, save maintenance costs, performance.

Language: Английский

Citations

0
Applications and challenges of digital twins of floating wind turbines DOI
Maria-Styliani Daraki, B. L. Mina,

Muhnad Almasoudi

et al.

Published: Jan. 1, 2024

A digital twin is a virtual model of physical asset, like wind turbine, synchronized with real-time data to provide insights into its performance, condition, and behavior. This technology has applications in environmental perception, condition assessment, predictive maintenance, anomaly detection, optimizing the operational parameters floating offshore turbines. paper reviews current state research practical twins this field. It explores concept, focusing on challenges posed by climate, system dynamics, structural issues Case studies include topics such as Fatigue Limit State, pitch blade control, drivetrain power output, strain. Technical implementing related collection, transfer, communication, standardization, well robustness models accurately simulating behaviors. Solutions can be found through AI, IoT, advanced simulation tools, improved monitoring techniques. Non-technical challenges, typical for emerging technologies, are mainly tied human factors. However, benefits financial advantages expected promote widespread adoption industrial applications.

Language: Английский

Citations

0