Climate change in recent years has produced viable shipping routes in the Arctic. However, critical uncertainties related to maritime operations in the Arctic make it difficult to predict ship speeds in ice and, thus, the voyage time and fuel costs. Cost–benefit analysis of alternative Arctic routes based on accurate environmental condition modeling is required. In this context, this paper presents a holistic approach that considers the major voyage-related costs of a trans-Arctic route as an alternative to the conventional routes via the Suez Canal Route (SCR) for existing merchant ships. This tool is based on high-fidelity models of ship performance, metocean forecasting, and a voyage optimization algorithm. Case studies are performed based on a general cargo vessel in operation to quantify realistic expenses inclusive of all the major operational, fuel, and voyage costs of the specific voyages. A comparison is made between the total costs of the trans-Arctic route and SCR for different seasons, which proves the economic feasibility of the trans-Arctic route. Overall, this work can provide valuable insights to help policymakers as well as shipbuilders, owners, and operators to assess the potential cost-effectiveness and sustainability of future Arctic shipping, thereby better developing future strategies.

The present paper introduces the development and verification of two ship performance models which have been implemented in a voyage planning tool designed for summer Arctic operations of commercial vessels. A novel ice resistance estimation algorithm for ice-floe conditions is implemented in the ship performance models. The fuel consumption predicted using both of the models are compared against full-scale measurements collected on a cargo ship of lower ice-class on the Northern Sea Route. This work found that both models meet the purpose of estimating ship fuel consumption for such a voyage planning tool and identified directions for future efforts. In addition, the typical transit scenarios in summer Arctic conditions presented in this study prove that a voyage planning tool with viable ship performance models facilitates Arctic shipping in a safe and sustainable way.

The Northeast Passage in the Arctic between Europe and Asia offers a significantly shorter voyage compared to the Southern route through the Suez Canal. In 2017, the EU research project “Safe maritime operations under extreme conditions: the Arctic case (SEDNA)” was established to perform a comprehensive analysis of Arctic transit shipping and to promote technical solutions for this purpose. This paper is based on the deliverables of the SEDNA project. A voyage planning tool (VPT) for Arctic applications was developed to plan the optimal route regarding ship’s fuel consumption and safety. One of the most advanced metocean and ice forecast model is utilized to provide comprehensive environmental conditions that are synchronized and will be updated frequently during the voyage. The ship energy system model takes into account the various environmental variables as well as ship’s operational conditions to compute the ship performance in both open and ice infested waters. For Arctic operations, specific ice resistance models are implemented in the VPT, and a user has the options of either relying on icebreaker assistance or going for unassisted navigation in part of the entire Arctic passage. Case study voyages of different ship types, route options, staring time, home/destination ports are simulated to demonstrate how various optimal routes are planned and how the transit time and fuel consumption vary. This information is considered being crucial for ship owners for planning their voyages in advance. The continuously updated voyage information from the VPT is particularly helpful for the ship crew if there are specific ship operations and risk mitigation actions that need to be taken care of during the voyage. In addition, this study underlines that a safe and fuel-efficient Arctic passage requires viable voyage planning tools that combine reliable ship performance with weather and ice forecasts.