Performance and Reliability Monitoring of Ship Hybrid Power Plants - Charalampos Tsoumpris; Gerasimos Theotokatos (Journal of Eta Maritime Science, 2022)
Recently, the marine industry has been under a paradigm shift toward adopting increased automation, and initiatives to enable the autonomous operations of ships are ongoing. In these cases, power plants require advanced monitoring techniques not only for the performance parameters but also to assess the health state of their critical components. In this respect, this study aims to develop a monitoring functionality for power plants that captures the performance metrics while considering the overall system and its components' reliability. A hybrid power plant of a pilot boat is considered a case study. A rule-based energy management strategy is adopted, which makes the decisions on the power distribution to the investigated power plant components. Additionally, a dynamic Bayesian network is developed to capture the temporal behavior of the system's/components' reliability accounting for the power plant's operating profile. Results demonstrate that the selected hybrid power plant monitoring capabilities are enhanced by providing the power plant performance along with the estimation of the system's health state. Furthermore, these extended monitoring capabilities can provide the essential metrics to facilitate decisionmaking, enabling the autonomous operation of the power plant.