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Medium-voltage direct-current (MVDC) ship-board microgrids (SMGs) are the state-of-the-art architecture for onboard power distribution in navy. These systems are considered to be highly dynamic due to high penetration of power electronic converters and volatile load patterns such as pulsed-power load (PPL) and propulsion motors demand variation. Obtaining the dynamic model of an MVDC SMG is a challenging task due to the confidentiality of system components models and uncertainty in the dynamic models through time. In this paper, a dynamic identification framework based on a temporal convolutional neural network (TCN) is developed to learn the system dynamics from measurement data. Different kinds of testing scenarios are implemented, and the testing results show that this approach achieves an exceptional performance and high generalization ability, thus holding substantial promise for development of advanced data-driven control strategies and stability prediction of the system.

Resilience is emerging as an evolving notion, reflecting a system's ability to endure and adapt to sudden and catastrophic changes and disruptions. This paper spotlights the significance of the quantitative resilience indices of medium-voltage DC (MVDC) distribution technology in marine vessels, notably naval ships. Given the intricate electrical requirements of modern naval ships, the need for a robust power supply underlines the imperative of resilient DC microgrids. Addressing this, our study introduces a novel quantitative metric for operational resilience of DC microgrids based on the measured voltage of main DC bus. This metric not only fuses real-time tracking, compatibility, and computational efficiency, but also adeptly monitors multiple event phases based on time-domain analysis of dc bus voltage dynamics. The intricacies of the dc bus voltage, including overshoots and undershoots, are meticulously accounted for in the algorithm design. With respect to existing research that typically focuses on offline resilience assessments, the proposed index provides valuable real-time information for microgrid operators and identifies whether microgrid resilience is deteriorating over time.

Future Naval Microgrids (MGs) will include hybrid energy storage systems (ESS), including battery and supercapacitors to respond to emerging constant power loads (CPLs) and fluctuating pulsed power loads (PPLs). Voltage regulation of naval microgrids and power sharing among these resources become critical for success of a mission. This paper presents a novel control strategy using nonlinear model predictive controller embedded with a complex droop control architecture for voltage restoration and power sharing in medium voltage DC (MVDC) Naval MGs. The complex droop control ensures allocating supercapacitors (SCs) for high-frequency loads (i.e., PPLs), while battery energy storage system (BESS) and auxiliary generators share the steady-state load (i.e., CPL). Compared to state-of-the-art control of the naval ship MGs that relies on linear models, the proposed method incorporates the nonlinear behavior of the MGs in the closed-loop control framework via nonlinear model predictive control (NMPC). A reduced order representation of the MVDC dynamic is employed as the prediction model, augmented with a multi-objective, constraints-based, optimal control formulation. The results demonstrate the effectiveness of the proposed control framework for voltage restoration and power sharing of resources in naval MGs.

DC shipboard microgrids (SMGs) are highly dynamic systems susceptible to failure due to various cyber-physical disturbances, such as extreme weather and mission operations during wartime. In this paper, the real-time operational resilience (OR) evaluation of DC SMGs against dynamic disturbances is proposed using frequency-domain metrics. To this end, first the drawbacks of time-domain OR evaluation using an energy imbalance index is discussed. As the time-domain energy imbalance index is shown to be incapable of real-time OR assessment, particularly in the context of droop-controlled DC SMGs without secondary voltage restoration control, the $\mathcal{H}_2$ and $\mathcal{H_\infty}$ norms of candidate transfer functions (TFs) of the system are proposed as measures of resilience. It is shown that the proposed norms calculated for the bus impedance TF of the system provides intuitive results in terms of energy imbalance and can be computed in real time. The case studies conducted for the study DC SMG under pulsed power load (PPL) disturbances demonstrate the shortcoming of the time-domain OR evaluation and the capability of the proposed frequency-domain metrics in intuitive OR evaluation of DC SMGs.