# Optimal Fleet Transition Modeling for Sustainable Inland Waterways Transport
## 1 Introduction
Each of these technologies brings its own unique set of characteristics and potential benefits, but all align with the broader objective of decarbonization. [PERSON] et al. [17] assessed diesel-versus electric-battery-powered inland vessels with and without photovoltaics for three vessel types. While electric vessels with photovoltaics had the lowest environmental impact, their life cycle costs were prohibitive for cargo and dredger vessels. However, for passenger vessels, battery electric power with photovoltaics was found to be a cost-effective, low-emission option. This suggests that electrification may be the most feasible strategy for sustainable transition of inland passenger fleets. This study focuses on the potential for electrifying the fleet at Orta lake, aiming to offer insights and methodologies that could be replicated in other maritime contexts across Europe. Orta lake, located in Italy, is one such local lake where inland waterways transport plays a relevant role for tourists' transportation. The lake's fleet is currently diesel-based, contributing to both local and global environmental impacts. The transition to a more sustainable fleet, specifically electric vessels, is therefore a pressing need. However, such a transition requires careful planning and optimization to ensure feasibility and effectiveness. In case of vessels in canals or lakes (\(\sim\)1000 t), scholars recommend the usage of lithium battery vessel technology with fast charging for short trips [17]. This paper aims to address this problem by developing an optimization model to determine the minimum number of electric vessels required to replace the existing diesel-based fleet entirely. This model is based on a comprehensive market analysis of available electric vessel models and their technical characteristics, such as capacity and range. The model is then applied to the case study of Orta lake, providing insights into the feasibility and implications of the transition. The optimization problem applied to the transition from diesel to electric vessels is done with a primary constraint, namely that the time schedule of vessels arrivals and departures remains unchanged. The shift towards sustainable alternatives in maritime transport fleets has garnered increasing attention in recent years. This transition is a critical aspect of broader efforts to reduce greenhouse gas emissions and mitigate climate change. While there is a substantial body of literature on optimizing sustainable transitions for public transport (e.g., buses) routes, similar research focusing specifically on maritime transport is not as extensive and has only begun to emerge more prominently in recent years. In the topic of sustainable transitions for bus routes, several studies have utilized mixed-integer linear models for optimization. For instance, a study [18] conducted an analysis of multiple bus routes at an urban level in Berlin, Germany, focusing on battery electric buses. The study considered parameters such as individual routes, bus types, and traffic, but did not delve into the impact of high slope variation or longer distances due to the specific topology of the case. Similarly, another study [19] employed a mixed-integer linear cost optimization model to explore the potential for substituting traditional public transportation modes with electric buses. This study focused on identifying the least energy-consuming routes and potential locations for electric bus infrastructure, assuming only constant slope values in a simplified road network. In a different approach, the authors of [20] developed a bi-objective model that minimizes both total carbon emission and operational cost for a mixed fleet of electric and diesel buses in the city of Liuzhou. While this study considered travel distance in their energy consumption model, it did not include slope considerations. A study [21] applied a mixed-integer nonlinear programming model to the transit network of Belleville city, Canada, with a detailed calculation of energy consumption for electric buses.