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Environmental pollution caused by ships’ green house gas emissions and worldwide concern about air quality and oil supplies have led to stricter emissions regulations and fuel economy standards. In this regard, respective limits are set, while efforts to provide general guidelines for the achievement of economic and green ship operation with an urge to ship operators to apply them and return feedback. Also, specific design and operation indicators have been proposed in order to ensure compliance with new emissions regulations and fuel economy standards. Up to now, these indices are limited to ships comprising conventional propulsion systems, while full electric propulsion systems are not examined. In this article, an integrated control system that attains economically optimized and environmentally friendly operation is proposed. Moreover, appropriate reformulation of energy efficiency operation indicator is proposed for real-time assessment of gas emissions. The study is supported with the presentation of results obtained from the simulation of the operation of a ship power system comprising full electric propulsion.

The popular radial basis function (RBF) neural network architecture and a new fast and efficient method for training such a network are used to model nonlinear dynamical multi-input multioutput (MIMO) discrete-time systems. The proposed training methodology is based on a fuzzy partition of the input space and combines self-organized and supervised learning. The algorithm is illustrated through the development of neural network models using simulated and experimental data. Results show that the methodology is much faster and produces more accurate models compared to the standard techniques used to train RBF networks. Another important advantage is that, for a given fuzzy partition of the input space, the proposed method is able to determine the proper network structure, without using a trial and error procedure.

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Research in All Electric Ship (AES) and onboard DC grids has already been initiated and it is going to be intensified because of its promising perspectives. This study aims to present in a coherent and methodical way why onboard DC distribution systems, smart grids and AES concept can greatly improve ship efficiency. Emerging technical challenges and future prospects are presented; state of the art is summarised while directions for a complete research roadmap are proposed.