TY - GEN
T1 - Optimizing Cruise Ship Speed Incorporating Weather and Hotel Load Factors
AU - Marashian, Arash
AU - Waris, Axel
AU - Razminia, Abolhassan
AU - Böling, Jari
AU - Manderbacka, Teemu
AU - Vettor, Roberto
AU - Huotari, Janne
AU - Gustafsson, Wilhelm
AU - Pirttikangas, Mathias
AU - Stigler, Claus
AU - Björkqvist, Jerker
AU - Manngård, Mikael
N1 - Publisher Copyright:
© 2024 EUCA.
PY - 2024
Y1 - 2024
N2 - In this paper, real-time weather and ship data will be used for mathematical modeling and cruise ship speed optimization. The ship data will be used for the construction of prediction models for hotel and auxiliary power consumption. Two different prediction model types will be compared: a simple polynomial model with linear parameters, as well as an artificial neural network. The effect of the ship's speed will be predicted using voyage optimization software, which takes into account weather and sea forecasts as well as the ship's hydrodynamic properties, for calculation of the required propulsion power as a function of speed. Total predicted power demand will be finally converted to fuel consumption, using information about the engine efficiencies. Furthermore, the associated cost will be attached to the edges of a graph, from which an optimal speed profile will be selected using dynamic programming. The performance of the models will be compared, and it is found that more than 3% of fuel savings are reported using both model types for the studied voyage.
AB - In this paper, real-time weather and ship data will be used for mathematical modeling and cruise ship speed optimization. The ship data will be used for the construction of prediction models for hotel and auxiliary power consumption. Two different prediction model types will be compared: a simple polynomial model with linear parameters, as well as an artificial neural network. The effect of the ship's speed will be predicted using voyage optimization software, which takes into account weather and sea forecasts as well as the ship's hydrodynamic properties, for calculation of the required propulsion power as a function of speed. Total predicted power demand will be finally converted to fuel consumption, using information about the engine efficiencies. Furthermore, the associated cost will be attached to the edges of a graph, from which an optimal speed profile will be selected using dynamic programming. The performance of the models will be compared, and it is found that more than 3% of fuel savings are reported using both model types for the studied voyage.
UR - http://www.scopus.com/inward/record.url?scp=85198214077&partnerID=8YFLogxK
U2 - 10.23919/ECC64448.2024.10591006
DO - 10.23919/ECC64448.2024.10591006
M3 - Conference contribution
AN - SCOPUS:85198214077
T3 - 2024 European Control Conference, ECC 2024
SP - 1642
EP - 1647
BT - 2024 European Control Conference, ECC 2024
PB - the Institute of Electrical and Electronics Engineers, Inc.
T2 - 2024 European Control Conference, ECC 2024
Y2 - 25 June 2024 through 28 June 2024
ER -