A Novel Wind Speed-Sensing Methodology for Wind Turbines Based on Digital Twin Technology

Li, Yang; Shen, Xiaojun

doi:10.1109/tim.2021.3139698

Cited by 18 publications

(9 citation statements)

References 29 publications

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“…In [63], an approach for the early-stage degradation of fuel cells and its prediction is addressed using DT, which is tolerant to different degradation patterns and can achieve real-time degradation prediction. The authors in [64] propose a novel wind speed-sensing methodology for wind turbines based on DT technology.…”

Section: Predictive Maintenance and Condition Monitoringmentioning

confidence: 99%

Review of Electric Vehicle Testing Procedures for Digital Twin Development: A Comprehensive Analysis

Rjabtšikov,

Rassõlkin,

Kudelina

et al. 2023

Energies

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This article explores the transformative potential of digital twin (DT) technology in the automotive sector, focusing on its applications in enhancing propulsion drive systems. DT technology, a virtual representation of physical objects, has gained momentum due to its real-time monitoring and analysis capabilities. Within the automotive industry, where propulsion systems dictate vehicle performance, DTs offer a game-changing approach. Propulsion drive systems encompass electric motors, transmissions, and related components, significantly impacting efficiency and power delivery. Traditional design and testing methods need help addressing these systems’ intricate interactions. This article aims to investigate how DTs can revolutionize propulsion systems. The study examines various applications of DTs, ranging from predictive maintenance to performance optimization and energy efficiency enhancement. The article underscores the technology’s potential by reviewing case studies and real-world implementations. It also outlines challenges tied to integration and validation. In unveiling the capabilities of DT technology for propulsion systems, this article contributes to a comprehensive understanding of its role in shaping a more data-driven and efficient automotive industry.

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Section: Predictive Maintenance and Condition Monitoringmentioning

confidence: 99%

Review of Electric Vehicle Testing Procedures for Digital Twin Development: A Comprehensive Analysis

Rjabtšikov,

Rassõlkin,

Kudelina

et al. 2023

Energies

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“…The historical data from sensors stored in AAS significantly contribute to predicting the wind speed (Hu et al, 2020;Li and Shen, 2022) and the future axial tension of mooring lines (Walker et al, 2021), and also to estimating the remaining useful life (RUL) of offshore wind farms (Mehlan et al, 2022). Branlard et al (2020b, a) presented digital twins of offshore wind farms in order to track the life cycle of the physical assets.…”

Section: The Interoperable Digital Twin Framework For the Offshore Wi...mentioning

confidence: 99%

“…For wind speed prediction, Hu et al (2020) applied digital twins to predicting time-series wind speed based on ensemble empirical model decomposition (EEMD), long short-term memory (LSTM) neural network, and the Bayesian Optimization (BO) method. Based on digital twin technology, Li and Shen (2022) proposed a novel wind speedsensing methodology for wind turbines by applying a series of estimators, verifiers, setters, and selectors called DTSense. Here, the digital twin is a digital replica that collects and stores operating data based on deep learning algorithms from physical assets to illustrate how an Internet of things (IoT) works through its life cycle.…”

mentioning

confidence: 99%

Industry 4.0 Digital Twins in Offshore Wind Farms

Ambarita,

Karlsen,

Scibilia

et al. 2023

Preprint

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Abstract. The use of digital twins in offshore wind farms presents a major opportunity to advance autonomous operations and optimize productivity. By creating virtual replicas of physical assets and systems, digital twins allow for real-time monitoring, predictive maintenance, and efficient decision-making. In the context of Industry 4.0, wind turbines are required not only to be remotely monitored and controlled through real-time data during operation, but also to manage the whole life cycle within the entire value chain. To accomplish this, the implementation of digital twin frameworks in accordance with Industry 4.0 standards is crucial. Motivated by the advanced technologies related to industrial digital twins in the context of Industry 4.0 implemented in the manufacturing sector, this paper presents findings from a study investigating the potential for transferring knowledge of industrial digital twins to offshore wind farm context. To gain a deeper understanding of the digital twin concept in the context of offshore wind applications, we conducted extensive literature studies. Specifically, we examined frameworks used in both the manufacturing industry and offshore wind industry. Our goal is to identify commonalities and differences between these frameworks, and to determine how they could be adapted to the unique requirements of the offshore wind sector. The Asset Administration Shell (AAS), which is a key concept of the Reference Architecture Model for Industry 4.0 (RAMI 4.0), provides a standardized and modular approach to representing and managing assets in industrial systems. By adopting AAS, offshore wind farms could improve the scalability, adaptability, and interoperability of their digital twin systems, and also enable more efficient and effective operation and maintenance of the turbines. Based on our findings, we concluded that implementing the AAS could be a promising option for enhancing the functionality of digital twins in offshore wind farms, and for achieving interoperability in line with the standards of Industry 4.0.

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“…Wind speed sensors are more error-prone, which deteriorates the performance of wind turbines and leads to faulty conditions. To detect fault sensors, Yang Li et al [47] proposed a data-driven digital twin estimating the wind speed for the downwind turbines based on the wind speed measurements at the upwind turbines and their spatiotemporal correlation. The residual between the estimated and measured speeds is used to identify a possible fault.…”

Section: Wind Energymentioning

confidence: 99%

A Comprehensive Review of Digital Twin Technology for Grid-Connected Microgrid Systems: State of the Art, Potential and Challenges Faced

et al. 2023

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The concept of the digital twin has been adopted as an important aspect in digital transformation of power systems. Although the notion of the digital twin is not new, its adoption into the energy sector has been recent and has targeted increased operational efficiency. This paper is focused on addressing an important gap in the research literature reviewing the state of the art in utilization of digital twin technology in microgrids, an important component of power systems. A microgrid is a local power network that acts as a dependable island within bigger regional and national electricity networks, providing power without interruption even when the main grid is down. Microgrids are essential components of smart cities that are both resilient and sustainable, providing smart cities the opportunity to develop sustainable energy delivery systems. Due to the complexity of design, development and maintenance of a microgrid, an efficient simulation model with ability to handle the complexity and spatio-temporal nature is important. The digital twin technologies have the potential to address the above-mentioned requirements, providing an exact virtual model of the physical entity of the power system. The paper reviews the application of digital twins in a microgrid at electrical points where the microgrid connects or disconnects from the main distribution grid, that is, points of common coupling. Furthermore, potential applications of the digital twin in microgrids for better control, security and resilient operation and challenges faced are also discussed.

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A Novel Wind Speed-Sensing Methodology for Wind Turbines Based on Digital Twin Technology

Cited by 18 publications

References 29 publications

Review of Electric Vehicle Testing Procedures for Digital Twin Development: A Comprehensive Analysis

Review of Electric Vehicle Testing Procedures for Digital Twin Development: A Comprehensive Analysis

Industry 4.0 Digital Twins in Offshore Wind Farms

A Comprehensive Review of Digital Twin Technology for Grid-Connected Microgrid Systems: State of the Art, Potential and Challenges Faced

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