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Abdullah F. Al-Aboosi, Aldo Jonathan Muñoz Vazquez, Fadhil Y. Al-Aboosi, Mahmoud El-Halwagi and Wei Zhan
Accurate prediction of renewable energy output is essential for integrating sustainable energy sources into the grid, facilitating a transition towards a more resilient energy infrastructure. Novel applications of machine learning and artificial intellig...
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Mohammad Barooni and Deniz Velioglu Sogut
The design and optimization of floating offshore wind turbines (FOWTs) pose significant challenges, stemming from the complex interplay among aerodynamics, hydrodynamics, structural dynamics, and control systems. In this context, this study introduces an...
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Dibo Dong, Shangwei Wang, Qiaoying Guo, Yiting Ding, Xing Li and Zicheng You
Predicting wind speed over the ocean is difficult due to the unequal distribution of buoy stations and the occasional fluctuations in the wind field. This study proposes a dynamic graph embedding-based graph neural network?long short-term memory joint fr...
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Rafael Pacheco-Blazquez, Julio Garcia-Espinosa, Daniel Di Capua and Andres Pastor Sanchez
This paper delves into the application of digital twin monitoring techniques for enhancing offshore floating wind turbine performance, with a detailed case study that uses open-source digital twin software. We explore the practical implementation of digi...
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Sheng Zhang, Guangzhong Liu and Chen Cheng
Over the past few decades, unmanned surface vehicles (USV) have drawn a lot of attention. But because of the wind, waves, currents, and other sporadic disturbances, it is challenging to understand and collect correct data about USV dynamics. In this pape...
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Ivan di Stefano, Daniele Durante, Paolo Cappuccio and Paolo Racioppa
The exploration of Uranus, a key archetype for ice giant planets and a gateway to understanding distant exoplanets, is acquiring increasing interest in recent years, especially after the Uranus Orbiter and Probe (UOP) mission has been prioritized in the ...
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Christy Pérez-Albornoz, Ángel Hernández-Gómez, Victor Ramirez and Damien Guilbert
Installation of new wind farms in areas such as the north coast of the Yucatan peninsula is of vital importance to face the local energy demand. For the proper functioning of these facilities it is important to perform wind data analysis, the data having...
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Peihua Xu, Maoyuan Zhang, Zhenhong Chen, Biqiang Wang, Chi Cheng and Renfeng Liu
Due to the increasing proportion of wind power connected to the grid, day-ahead wind power prediction plays a more and more important role in the operation of the power system. This paper proposes a day-ahead wind power short-term prediction model based ...
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Juan M. Lujano-Rojas, Rodolfo Dufo-López, Jesús Sergio Artal-Sevil and Eduardo García-Paricio
Assessing the training process of artificial neural networks (ANNs) is vital for enhancing their performance and broadening their applicability. This paper employs the Monte Carlo simulation (MCS) technique, integrated with a stopping criterion, to const...
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Jingjing Liu, Xinli Yang, Denghui Zhang, Ping Xu, Zhuolin Li and Fengjun Hu
Multi-node wind speed forecasting is greatly important for offshore wind power. It is a challenging task due to unknown complex spatial dependencies. Recently, graph neural networks (GNN) have been applied to wind forecasting because of their capability ...
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