Fuel-Optimal Thrust-Allocation Algorithm Using Penalty Optimization Programing for Dynamic-Positioning-Controlled Offshore Platforms

Se Won Kim and Moo Hyun Kim
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Se Won Kim: Daewoo Shipbuilding and Marine Engineering Co., LTD., 125, Namdaemun-ro, Jung-gu, Seoul 04521, Korea
Moo Hyun Kim: Ocean Engineering, Texas A&M University, College Station, TX 77843, USA

Energies, 2018, vol. 11, issue 8, 1-24

Abstract: This research, a new thrust-allocation algorithm based on penalty programming is developed to minimize the fuel consumption of offshore vessels/platforms with dynamic positioning system. The role of thrust allocation is to produce thruster commands satisfying required forces and moments for position-keeping, while fulfilling mechanical constraints of the control system. The developed thrust-allocation algorithm is mathematically formulated as an optimization problem for the given objects and constraints of a dynamic positioning system. Penalty programming can solve the optimization problems that have nonlinear object functions and constraints. The developed penalty-programming thrust-allocation method is implemented in the fully-coupled vessel–riser–mooring time-domain simulation code with dynamic positioning control. Its position-keeping and fuel-saving performance is evaluated by comparing with other conventional methods, such as pseudo-inverse, quadratic-programming, and genetic-algorithm methods. In this regard, the fully-coupled time-domain simulation method is applied to a turret-moored dynamic positioning assisted FPSO (floating production storage offloading). The optimal performance of the penalty programming in minimizing fuel consumption in both 100-year and 1-year storm conditions is demonstrated compared to pseudo-inverse and quadratic-programming methods.

Keywords: dynamic positioning; thrust allocation; turret-moored FPSO; penalty programming; optimization; pseudo-inverse; quadratic-programming; fuel consumption; genetic algorithm; thruster arrangement (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
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