Optimal weather routing using ensemble weather forecasts
2015 (English)Licentiate thesis, comprehensive summary (Other academic)
Ships small and large all battle the elements when crossing the worlds oceans. As such, ships are designed to operate in situations with high speed winds and heavy waves. There are however limits to what any ship can handle safely and it is thus important to avoid the worst weather systems as much as possible. To do this ships are routed using weather data, gathered as statistical seasonal averages or numerical forecasts, in a process called weather routing. With increased capabilities to model ship performance and seakeeping numerically, using computers, weather routing evolved to what is usually called route optimization. In route optimization weather forecasts are used to compute the most ecient route. How to determine which route is most ecient is up to the ship operator, usually some combination of fuel consumption and sailing time is used together with constraints related to safety. This thesis explores the implications of unreliability in weather forecasts on route optimization and howensemble weather forecastsmay be used to improve route optimization.
In paper A a route optimization method that uses the ensemble weather forecast to compute routes is developed and tested against standard route optimization methods. The results show that routes optimized using the ensemble weather forecasts are more reliable in their predictions of fuel consumption and arrival time at the destination.
In paper B the relationship between forecast reliability and the risk of late arrival is explored through the use of arobustnessmeasure based on the ensemble weather forecast.
In paper C the research presented inpaper Bis continued and extended. The relationship between therobustnessof a route and the likelihood of late arrival is investigated. The eect of seakeeping constraints on the robustnessmeasure is explored. Finally a method of using the robustnessmeasure for route optimization is developed and tested. The results show that this method can reduce the risk of late arrival without increasing fuel consumption on average.
Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. , viii, 9 p.
TRITA-AVE, ISSN 1651-7660 ; 2015:87
route optimization, ensemble weather forecasts
IdentifiersURN: urn:nbn:se:kth:diva-177332ISBN: 978-91-7595-773-9OAI: oai:DiVA.org:kth-177332DiVA: diva2:872291
2015-12-11, Munin, Teknikringen 8, KTH, Stockholm, 10:00 (English)
Mao, Wengang, Docent
Kuttenkeuler, Jakob, ProfessorRosén, Anders, Docent
FunderThe Swedish Mercantile Marine Foundation
QC 201511202015-11-202015-11-182015-11-20Bibliographically approved
List of papers