This study proposes a new application for delay-dependent stability analysis of a shipboard microgrid system. Gain and phase margin values are taken into consideration in delay dependent stability analysis. Since such systems are prone to unwanted frequency oscillations against load disturbances and randomness of renewable resources, a virtual gain and phase margin tester has been incorporated into the system to achieve the desired stabilization specification. In this way, it is considered that the system provides the desired dynamic characteristics (e.g. less oscillation, early damping, etc.) in determining the time delay margin. Firstly, the time delay margin values are obtained and their accuracy in the terms of desired gain and phase margin values are investigated. Then, the accuracy of the time delay margin values obtained by using the real data of renewable energy sources and loads in the shipboard microgrid system is shown in the study. Finally, a real-time hardware-in-the-loop (HIL) simulation based on OPAL-RT is accomplished to affirm the applicability of the suggested method, from a systemic perspective, for the load frequency control problem in the shipboard microgrid.
The power system of an all-electric ship (AES) establishes an independent microgrid using the distributed energy resources, energy storage devices, and power electronic converters. As a hybrid energy system (HES), the power system of an AES works as a unified system where each part can affect the reliability of the other parts. The systemic reliability centered maintenance (SRCM), which efficiently enhances the reliability and safety of the AES by identifying optimal maintenance tasks of the AES, is considered in this article to apply to the entire system. In order to calculate the reliability and optimal maintenance schedule, the Markov process and Enhanced JAYA (EJAYA) are utilized. A layer of protection analysis (LOPA), which is a risk management technique, is adopted to assess the safety of the system. A hybrid molten carbonate fuel cell, photovoltaic (PV), and lithium-ion battery are considered as energy sources of the AES. Based on two common standards, DNVGL-ST-0033 and DNVGL-ST-0373, the suggested maintenance planning method can be used in industrial applications. Eventually, in order to validate the proposed method, a model-in-the-loop real-time simulation using dSPACE is carried out. The obtained results show the applicability and efficiency of the proposed method for improving reliability and safety.
The utilization of green energy resources for supplying energy to ships in the marine industry has received increasing attention during the last years, where different green resource combinations and control strategies have been used. This article considers a ferry ship supplied by fuel cells (FCs) and batteries as the main sources of ship's power. Based on the designers' and owners' preferences, different scenarios can be considered for managing the operation of the FCs and batteries in all-electric marine power systems. In this article, while considering different constraints of the system, six operating scenarios for the set of FCs and batteries are proposed. Impacts of each proposed scenario on the optimal daily scheduling of FCs and batteries and operation costs of the ship are calculated using a mixed-integer nonlinear programming model. Model predictive control (MPC) is also applied to consider the deviations from hourly forecast demand. Moreover, since the efficiency of FCs varies for different output powers, the impacts of applying a linear model for FCs' efficiency are compared with the proposed nonlinear model and its related deviations from the optimal operation of the ship are investigated. The proposed model is solved by GAMS software using actual system data and the simulation results are discussed. Finally, detailed real-time hardware-in-the-loop (HiL) simulation outcomes and comparative analysis are presented to confirm the adaptation capability of the proposed strategy.