A Communication-Less Multimode Control Approach for Adaptive Power Sharing in Ship-Based Seaport Microgrid

The increase in greenhouse gas emissions from the transportation sector together with the continued depletion of fossil fuels in general has encouraged an increase in the use of energy storage systems and renewable energy sources at seaports and also on short route yachts and ferries. At present, most seaports, particularly smaller ones, are not provided with cold-ironing facilities - shore-based power facilities, which provide electric power to ships from the national grid. Because of the lack of cold-ironing facilities at most ports, auxiliary diesel engines and diesel generators on ships must be kept operating and online while at berth to supply auxiliary loads of ship. To address these requirements, one possible solution would be to provide cold-ironing facilities at all ports. However, in many circumstances, this is not cost-efficient as a port might be far from the national grid. To overcome these limitations, a seaport microgrid can be formed through the integration of multiple shipboard microgrids (SMGs) with decentralized control together with a charging infrastructure that is located on-shore. This integration of multiple SMGs and port-based charging stations is termed a ship-based seaport microgrid. Typically, power is shared among different microgrids using data communication techniques, which adds to the cost and the complexity of the overall system. This article proposes a communication-less approach based on multimode, decentralized droop control that enables power sharing among several SMGs in both charging and discharging modes based on the state of charge of battery banks - electric power is either supplied or consumed. The proposed approach would be potentially useful for future autonomous ships and also for islands where port electrification is either not technically feasible or an economically viable solution. A simulation and hardware-in-the-loop results are provided to verify the control robustness of the proposed control strategy.