Optimal ship lifetime fuel and power system selection under uncertainty

Lagemann, Benjamin; Lagouvardou, Sotiria; Lindstad, Elizabeth; Fagerholt, Kjetil; Psaraftis, Harilaos N.; Erikstad, Stein Ove

doi:10.1016/j.trd.2023.103748

Cited by 11 publications

(9 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The stochastic programming model is a bi-objective two-stage optimization model. The full model including all constraints is described in detail by [17]. From the deterministic model presented above, two additional steps are required to derive the mathematical formulation for the stochastic programming model.…”

Section: Stochastic Optimizationmentioning

confidence: 99%

“…That is, the model applies a risk-neutral expected value formulation. The scenarios are sampled based on the probability distributions discussed in [17]. The sampling of scenarios from probability distributions implies that probabilities are implicit in the scenario set.…”

Section: Stochastic Optimizationmentioning

confidence: 99%

“…The economic impact has an operational part which includes an uncertain range that has been based on estimates from [8,27] and a fixed capital cost part. The retrofit cost has been elaborated in [17]. The new build, lost opportunity, fuel consumption and retrofit costs should be recalculated for vessels of different size and function.…”

Section: Input Datamentioning

confidence: 99%

“…Further inputs required for the stochastic model are the probability density functions for both fuel costs and carbon prices. As described in [17], a triangular function is assumed for the fuel costs, and a beta-variate distribution (alpha 1.5, beta 5) is selected for the carbon prices up to 1000 USD/tCO 2eq . The beta-variate distribution peaks at about 100 USD/tCO 2eq .…”

Section: Input Datamentioning

confidence: 99%

See 3 more Smart Citations

Optimal Ship Fuel Selection under Life Cycle Uncertainty

Zwaginga,

Lagemann,

Erikstad

et al. 2024

Sustainability

Self Cite

View full text Add to dashboard Cite

Shipowners need to prepare for low-emission fuel alternatives to meet the IMO 2050 goals. This is a complex problem due to conflicting objectives and a high degree of uncertainty. To help navigate this problem, this paper investigates how methods that take uncertainty into account, like robust optimization and stochastic optimization, could be used to address uncertainty while taking into account multiple objectives. Robust optimization incorporates uncertainty using a scalable measure of conservativeness, while stochastic programming adds an expected value to the objective function that represents uncertain scenarios. The methods are compared by applying them to the same dataset for a Supramax bulk carrier and taking fuel prices and market-based measures as uncertain factors. It is found that both offer important insights into the impact of uncertainty, which is an improvement when compared to deterministic optimization, that does not take uncertainty into account. From a practical standpoint, both methods show that methanol and LNG ships allow a cheap but large reduction in emissions through the use of biofuels. More importantly, even though there are limitations due to the parameter range assumptions, ignoring uncertainty with respect to future fuels is worse as a starting point for discussions.

show abstract

Section: Stochastic Optimizationmentioning

confidence: 99%

Section: Stochastic Optimizationmentioning

confidence: 99%

Section: Input Datamentioning

confidence: 99%

Section: Input Datamentioning

confidence: 99%

See 2 more Smart Citations

Optimal Ship Fuel Selection under Life Cycle Uncertainty

Zwaginga,

Lagemann,

Erikstad

et al. 2024

Sustainability

Self Cite

View full text Add to dashboard Cite

show abstract

“…Compared to studies covering all or nearly all abatement options [21,23], some options are not considered in this paper, such as biofuels, or any fuel saving measures such as design optimization, technical improvement or voyage optimization. Some studies [24,25,26] indicate that biofuels can be an economically favorable way to abate emissions from shipping as well as aviation [10]. In this paper, we focus on the fundamental trade-offs regarding the use of renewable electricity in decarbonization solutions.…”

Section: Background: Transport Ghg Abatement Scenariosmentioning

confidence: 99%

Smart use of renewable electricity and carbon capture in the transport sector

Lindstad,

Lagemann,

Rialland

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

The decarbonization of the transport sector, which accounts for a quarter of global energy use when including its fuel production and consumption, is critical to limit global temperature rise well below 2 degrees. Building on the positive impact of battery-electric solutions on decarbonizing road transport, this study explores the potential expansions of zero-emission solutions to aviation and maritime shipping through the utilization of advanced E-fuels produced with renewable electricity. We analyze whether using renewables to produce E-fuels delivers carbon reductions in a more energy-effective way than Carbon Capture onboard sea-going vessels and Direct Air Carbon Capture at land-based facilities, both combined with permanent storage. Our analysis reveals that Carbon Capture and Storage requires significantly less renewable electricity and hence should be prioritized in shipping and aviation. This will enable renewable electricity to be used within other sectors which will give faster global decarbonization.

show abstract