A health-aware energy management strategy for autonomous ships power plants operation

Abstract

This study focuses on the development of a health-aware energy management strategy for the operation of autonomous ship power plants. To enable autonomous decisions, it is essential to acquire sufficient situational awareness based on the machinery health state. In this respect, a dynamic Bayesian network (DBN) approach is adopted to calculate the components and system reliability. The predictive information along with the operating profile are considered in an enhanced energy management strategy, based on the equivalent consumption minimisation strategy (ECMS). To demonstrate the applicability of the proposed approach, a parallel hybrid power plant is selected as a case study. The results demonstrate that the most critical component is the engine. By using the proposed strategy, the degradation of the engine can be attenuated, and the plant operation in safer regions can be achieved.