Analysis of Truck Electrification in the Port of Mussalo

Abstract

This report presents an assessment of external truck traffic estimation associated with Mussalo Port and examines the implications of partial electrification of heavy-duty freight vehicles for charging infrastructure demand and electricity grid capacity. The study is based on traffic observations obtained from Fintraffic Traffic Measurement Stations (TMS) located along the logistics corridors that serve the port area. These stations provide raw data containing vehicle movement constraints. To address these data constraints, the analysis applies an inference-based framework to identify truck movements that are associated with port activity. The traffic dataset is first restricted to heavy vehicles, and passenger cars and light-duty vehicles are excluded. This filtering step aligns the dataset with the focus on freight transport and charging demand. Following this, truck movements are inferred through probabilistic matching between pairs of traffic measurement stations. Matching is performed statistically using constraints and feasible travel time windows derived from known distances between stations. Truck observations that satisfy these conditions across multiple stations are treated as matched movements along logistics corridors, while observations that do not satisfy these conditions are classified as unmatched traffic. The matched truck flows are further processed to identify vehicles that can be considered candidates for battery-electric operation. This screening is based on vehicle class, haul length, and duty cycle assumptions. Electrification scenarios are constructed using class-wise adoption assumptions rather than a single penetration rate applied across all vehicles. This approach allows electrification to be represented in terms of absolute truck counts rather than aggregated percentages. Charging demand is estimated for the electrified truck subset using assumptions related to battery capacity, state of charge at arrival, target state of charge after charging, charging efficiency, and charging frequency. Two charging cases are evaluated to represent different operational conditions. For each case, annual energy consumption and peak power demand are calculated at the site level. The results indicate that peak power demand, rather than total annual energy consumption, determines charging infrastructure requirements and grid connection constraints at Mussalo Port.