Energy Flow Control And Sizing Of A Hybrid Battery/Supercapacitor Storage In Mvdc Shipboard Power Systems

The propulsion system of a medium-voltage dc (MVDC) ship is subject to large thrust/torque variations due to interactions of the ship and the propeller with sea waves. These variations induce steep power fluctuations on the MVDC bus, adversely impacting the stability, efficiency and power quality. Hybrid energy storage system (HESS) is a promising solution for mitigating these power fluctuations. Dictating the energy that the HESS components must deliver/absorb, the energy management strategy (EMS) impacts the size/capacity of the energy storage system (ESS). Based on this consideration, sizing and EMS of a battery/supercapacitor (SC) HESS are jointly optimised by using a deep reinforcement learning-based method. The proposed method splits the power between the HESS components such that while the operational constraints are satisfied, energy storage size and losses are minimised. Its features are adaptability to varying sea states, real-time implementation feasibility, while obviating the requirement for knowledge of the ship propulsion power profile. The efficacy of the joint sizing/EMS on reducing the ESS size is validated by comparing the sizes when battery-only, SC-only and HESS are employed in the MVDC shipboard power system. Real-time implementation feasibility and adaptability to various ship propulsion power profiles is confirmed through real-time simulations.