An Efficient Framework for Improving Microgrid Resilience against Islanding with Battery Swapping Stations

In this paper, an efficient bi-level framework is proposed to enhance the resilience of microgrids (MGs) against islanding due to low probability-high impact events by incorporating battery swapping stations (BSSs). In the emergency condition, MG solves the upper-level of the proposed model to report the desired energy transaction including surplus energy and unsupplied loads during the islanding period to the BSSs coordinator. The lower-level problem will be solved with an iterative algorithm by BSSs coordinator to report different plans of energy transactions and their prices to the MG during the emergency period. The price of each energy transaction plan is determined based on a bonus mechanism. Finally, MG will choose the best plan of energy trading considering a new proposed perspective of resilience improvement. Furthermore, a new formulation for BSS operation with fewer variables in comparison to the previous works is proposed in this paper. Simulations are carried out on an MG with two BSSs to verify the proposed model

Review of dynamic positioning control in maritime microgrid systems

For many offshore activities, including offshore oil and gas exploration and offshore wind farm construction, it is essential to keep the position and heading of the vessel stable. The dynamic positioning system is a progressive technology, which is extensively used in shipping and other maritime structures. To maintain the vessels or platforms from displacement, its thrusters are used automatically to control and stabilize the position and heading of vessels in sea state disturbances. The theory of dynamic positioning has been studied and developed in terms of control techniques to achieve greater accuracy and reduce ship movement caused by environmental disturbance for more than 30 years. This paper reviews the control strategies and architecture of the DPS in marine vessels. In addition, it suggests possible control principles and makes a comparison between the advantages and disadvantages of existing literature. Some details for future research on DP control challenges are discussed in this paper

A Deep Learning Method for Short-Term Dynamic Positioning Load Forecasting in Maritime Microgrids

The dynamic positioning (DP) system is a progressive technology, which is used in marine vessels and maritime structures. To keep the ship position from displacement in operation mode, its thrusters are used automatically to control and stabilize the position and heading of vessels. Hence, the DP load forecasting is already an essential part of DP vessels, which the DP power demand from the power management system (PMS) for thrusting depends on weather conditions. Furthermore, the PMS is used to control power generation, and prevent power failure, limitation. To perform station keeping of vessels by DPS in environmental changes such as wind, waves, capacity, and reliability of the power generators. Hence, a lack of power may lead to lower DP performance, loss of power, and position, which is called shutdown. Therefore, precise DP power demand prediction for maintaining the vessel position can provide the PMS with sufficient information for better performance in a complex decision-making process for the DP vessel. In this paper, the concept of deep learning techniques is introduced into DPS for DP load forecasting. A Levenberg–Marquardt algorithm based on a nonlinear recurrent neural network is employed in this paper for predicting thrusters’ power consumption in sea state variations due to challenges in power generation with the relative degree of accuracy by combining weather parameter dependencies as environmental disturbances. The proposed method evaluates with three traditional forecasting methods through a set of practical real-time DP load and weather parametric data. Numerical analysis has shown that with the proposed method, the future DP load behavior can be predicted more accurately than that obtained from the traditional methods, which greatly assists in operation and planning of power system to maintain system stability, security, reliability, and economics