Hybrid Energy Storage Energy Management Collaborative Optimization Method for Improving Power Quality in Ship Power Grids

Aiming at the challenge that the traditional single energy storage scheme can hardly meet the power quality demand under complex working conditions, this paper proposes a multi-objective co-optimization technique grounded in the non-dominated sorting genetic algorithm (NSGA-II) for hybrid energy storage in ship DC integrated power systems. In this paper, second-order filtering is adopted as the approach for handling energy administration. Next, developing a collaborative optimization framework that takes into account the interrelated aspects of capacity distribution and energy management tactics. Besides, the optimal filter coefficients and optimal energy storage capacity are solved by NSGA-II. Ultimately, the proposed method was evaluated through a simulation model, and the findings indicated that it not only curbs power fluctuations more effectively, but also enhances the quality of the ship’s electrical grid, diminishes the DC bus voltage variations, and ensures that the system’s investment costs are kept to a minimum.