Marine energy digitalization digital twin's approaches

• Published in: Renewable & sustainable energy reviews 2024-03, Vol.191, p.114065, Article 114065
• Main Authors: Majidi Nezhad, Meysam, Neshat, Mehdi, Sylaios, Georgios, Astiaso Garcia, Davide
• Format: Article
• Language: English
• Subjects: Applications and platforms; Artificial Intelligence; Digital twins; Energy digitalization; European Countries; Marine energy
• ISSN: 1364-0321; 1879-0690
• DOI: 10.1016/j.rser.2023.114065

Digital twins (DTs) promise innovation for the marine renewable energy sector using modern technological advances and the existing maritime knowledge frameworks. The DT is a digital equivalent of a real object that reflects and predicts its behaviours and states in a virtual space over its lifetime. DTs collect data from multiple sources in pilots and leverage newly introduced low-cost sensor systems. They synchronize, homogenize, and transmit the data to a central hub and integrate it with predictive and learning models to optimize plant performance and operations. This research presents critical aspects of DT implementation challenges in marine energy digitalization DT approaches that use and combine data systems. Firstly, the DT and the existing framework for marine knowledge provided by systems are presented, and the DT's main development steps are discussed. Secondly, the DT implementing main stages, measurement systems, data harmonization and preprocessing, modelling, comprehensive data analysis, and learning and optimization tools, are identified. Finally, the ILIAD (Integrated Digital Framework for Comprehensive Maritime Data and Information Services) project has been reviewed as a best EU funding practice to understand better how marine energy digitalization DT's approaches are being used, designed, developed, and launched.