Risk management is a critical activity in the dynamic positioning (DP) industry, and the success or failure of the risk management strategy relies on knowing the consequences of possible risk events. This article proposes a novel multi-objective power plant optimization system based on a consequence analysis machine for DP with a battery-powered hybrid propulsion. The motivation of this article is to answer the question “How should we operate a DP vessel after engaging the battery powered energy storage system?” Unlike, a conventional consequence analysis machine, the proposed strategy not only gives a pass or fail criterion but also calculates the thrust safety margin as a key factor quantifying the DP system’s station keeping capability after the worst-case failure. A multi-objective optimization model is implemented into a hybrid power plant model using a real-time data analysis. The objectives of this optimization are set to: (a) maximize the thrust margin, (b) minimize the power plant fuel consumption, (c) minimize the greenhouse gas emission, and (d) predict the duration of operation after a failure. The analysis provides DP operators a graded and ranked list of generator and bus configurations. Depending on the criticality of the current vessel operation, the operator can turn on/off generators and open/close tie breakers accordingly.
No takes yet. Share an insight, caveat, or question.
Bourgeau et al. (2025) studied this question.
Synapse has enriched 5 related papers. Consider them for comparative context: