A decision-making approach for the health-aware energy management of ship hybrid power plants
Charalampos Tsoumpris, Γεράσιμος Θεοτοκάτος
Abstract
Although autonomous shipping has attracted increasing interest, its further development requires innovative solutions to operate autonomous ships without the direct intervention of human operators. This study aims to develop a health-aware energy management (HAEM) approach for ship hybrid power plants, integrating the health monitoring information from reliability tools with the energy management tools. This approach employs the equivalent consumption minimisation strategy (ECMS) along with a Dynamic Bayesian network (DBN), as well as the utopia decision-making method and a model for the ship hybrid power plant. The HAEM approach is demonstrated for a parallel hybrid power plant of a pilot boat considering realistic operating profiles. The results demonstrate that by employing HAEM approach for the investigated ship power plant operating for 300 h reduces its failure rate almost fourfold at the cost of fuel consumption increase of around 1.5%, compared to the respective operation with the ECMS. This study is expected to contribute towards the development of supervisory control of autonomous power plants.