Retrofit modeling for green ships

Abstract

This paper proposes a data-driven approach to reduce emissions in international shipping, aligning with the IMO's goal of achieving net-zero greenhouse gas emissions by around 2050. Digital twins (DTs) offer promise for maritime decarbonization due to their simulation and big data handling capabilities. However, fully realizing DTs for new-build is by definition challenging as it requires a real-time data connection. Thus, the research begins with retrofitting existing ships using operational data collected through Bunker Delivery Notes (BDNs), a mandatory method for larger ships since January 2019. The proposed framework constructs digital models to support the retrofit DT, that are tested on a 300m bulk carrier. A fuel consumption model is built using a gray box approach, while various wind-assisted ship propulsion systems are modeled using a white box approach. The study evaluates the design implications and emissions reduction potential of implementing these systems.