Work

Digital twins and AI integration in offshore renewable energy: A Review

Year: 2025

Type: conference-paper

Abstract: The integration of digital twins and AI in offshore renewable energy systems represents a transformative approach to improve operational efficiency, scalability, and sustainability. This paper provides a review of innovative applications of digital twins and AI in the context of offshore wind energy and floating energy islands. It examines the existing literature and published case studies to highlight the challenges in this field. Digital twins are revolutionizing the design, monitoring, and maintenance of offshore platforms. By incorporating AI-driven analytics and predictive maintenance capabilities, these systems enable precise decision-making, reduce downtime, and extend the lifespan of infrastructure subjected to harsh marine environments. Case studies discussed include the application of digital twins for structural health monitoring in offshore wind farms, where significant reductions in maintenance costs were achieved through predictive analytics.

Source: IOP Conference Series Earth and Environmental Science

DOI: 10.1088/1755-1315/1552/1/012007

Authors: Milena Rajić, Marko Mančić, Anina Glumac, Mosè Rossi, Carlos Rebelo

Institutions: University of Nis, University of Belgrade, Marche Polytechnic University, University of Coimbra

Language: English

Topic: Wave and Wind Energy Systems

Subfield: Ocean Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Affordable and clean energy, Industry, innovation and infrastructure, Climate action

Open Access status: diamond

OpenAlex ID: W4416420001

FWCI: 2.96

Cites: 34

Cited by: 1

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