Abstract
Abstract Paper aims This paper studies a new optimization problem called the Electric Boat Charging Problem (EBCP), which is based on the application of electric mobility in a river transport operation problem. Originality This work pioneers the studies of the electric mobility on the river operations, by proposing the EBCP. This problem includes real features of the electric mobility such as nonlinear charging functions, battery degradation costs, and speed variation. Research method For solving the EBCP, we propose a Mixed-Integer Linear Programming (MILP) formulation. For testing our MILP formulation, we use a set of instances based on a future transport operation. We also analyze the impact of some problem parameters on the objective function, and decision variables. Main findings Our MILP formulation is capable to optimally solve different type of instances in competitive CPU times. The battery capacity and a time limit constraint have and important impact on the objective function and the decision-making variables. Implications for theory and practice We model the EBCP as a MILP formulation. This model allows to optimally solve industrial scale instances. Moreover, using a sensitivity analysis, we unveil that both the battery capacity and the time limit constraint of the EB route are critical parameters.
Highlights
Nowadays, air pollution and greenhouse gas emissions are a major concern given their impact on human health and global warming
Paper aims: This paper studies a new optimization problem called the Electric Boat Charging Problem (EBCP), which is based on the application of electric mobility in a river transport operation problem
It is important to notice that Internal Combustion Boats (ICBs) cost only accounts the fuel cost; ICBs have a related Social Cost of Carbon (SCC)
Summary
Air pollution and greenhouse gas emissions are a major concern given their impact on human health and global warming. Jaimurzina et al (2017) studied the insertion of electric mobility alternatives for river transport in Latin America They present a technological solution including considerations of generation and autonomy. For the smart decision making on EB speed and where/how much to charge, we solve an optimization problem that we call the Electric Boat Charging Problem (EBCP) In this problem, the objective function is to minimize the sum of the costs of the charged energy plus battery degradation costs, taking into account autonomy and the time limit constraints. The objective function is to minimize the sum of the costs of the charged energy plus battery degradation costs, taking into account autonomy and the time limit constraints For solving this optimization problem, we propose a Mixed-Integer Linear Programming (MILP) model.
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